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  "signature": "sha256:e08b12848697c65e49d9bca292a4de704dbee095dda617212ed6928cbb990b84"
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import pandas as pd\n",
      "from os.path import join\n",
      "\n",
      "from pylab import rcParams\n",
      "import matplotlib.pyplot as plt\n",
      "%matplotlib inline\n",
      "rcParams['figure.figsize'] = (16, 8)\n",
      "\n",
      "import nilmtk\n",
      "from nilmtk import DataSet, TimeFrame, MeterGroup, HDFDataStore\n",
      "from nilmtk.disaggregate import CombinatorialOptimisation\n",
      "from nilmtk.utils import print_dict\n",
      "from nilmtk.metrics import f1_score\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings(\"ignore\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Demo of NILMTK v0.2 for BuildSys 2014"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Downloading data"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The full data set can be downloaded from the remote WikiEnergy database. The credentials are omitted here for security reasons."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# download_wikienergy(database_username, database_password, hdf_filename)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Loading data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data_dir = '/home/nipun/Downloads/'\n",
      "we = DataSet(join(data_dir, 'wikienergy.h5'))\n",
      "print('loaded ' + str(len(we.buildings)) + ' buildings')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "loaded 239 buildings\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine dataset metadata"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print_dict(we.metadata)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<ul><li><strong>meter_devices</strong>: <ul><li><strong>eGauge</strong>: <ul><li><strong>max_sample_period</strong>: 120</li><li><strong>description</strong>: Measures circuit-level power demand.  Comes with 12 CTs.\n",
        "</li><li><strong>manufacturer_url</strong>: <a href=\"https://www.egauge.net\">https://www.egauge.net</a></li><li><strong>measurements</strong>: <ul><li>{'type': 'active', 'upper_limit': 5000, 'lower_limit': 0, 'physical_quantity': 'power'}</li></ul></li><li><strong>sample_period</strong>: 60</li><li><strong>wireless</strong>: False</li><li><strong>model</strong>: eGauge</li><li><strong>manufacturer</strong>: eGauge Systems LLC</li></ul></li></ul></li><li><strong>creators</strong>: <ul><li>Jim Shead</li></ul></li><li><strong>name</strong>: WikiEnergy</li><li><strong>description</strong>: Several months of power data for more than 239 different homes.</li><li><strong>number_of_buildings</strong>: 239</li><li><strong>related_documents</strong>: <ul><li><a href=\"http://wiki-energy.org/\">http://wiki-energy.org/</a></li><li><a href=\"http://wiki-energy.org/wp-content/uploads/2014/02/20140610-WikiEnergy-Exporting-Data-Instructions.pdf\">http://wiki-energy.org/wp-content/uploads/2014/02/20140610-WikiEnergy-Exporting-Data-Instructions.pdf</a></li><li><a href=\"http://wiki-energy.org/wp-content/uploads/2014/02/Database-Descriptions-20140319.pdf\">http://wiki-energy.org/wp-content/uploads/2014/02/Database-Descriptions-20140319.pdf</a></li></ul></li><li><strong>long_name</strong>: WikiEnergy database</li><li><strong>contact</strong>: jshead@pecanstreet.org</li><li><strong>geo_location</strong>: <ul><li><strong>latitude</strong>: 30.292308</li><li><strong>country</strong>: US</li><li><strong>longitude</strong>: -97.699671</li><li><strong>locality</strong>: Austin</li></ul></li><li><strong>publication_date</strong>: 2014</li><li><strong>timezone</strong>: US/Central</li><li><strong>schema</strong>: <a href=\"https://github.com/nilmtk/nilm_metadata/tree/v0.2\">https://github.com/nilmtk/nilm_metadata/tree/v0.2</a></li><li><strong>institution</strong>: Pecan Street Inc</li><li><strong>subject</strong>: Disaggregated power demand from domestic buildings.</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f411004cf50>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine metadata for a single house"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "building_number = 11\n",
      "print_dict(we.buildings[building_number].metadata)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<ul><li><strong>instance</strong>: 11</li><li><strong>dataset</strong>: WikiEnergy</li><li><strong>original_name</strong>: 434</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f411004ca10>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine sub-metered appliances"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec = we.buildings[building_number].elec\n",
      "elec.appliances"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "[Appliance(type='fridge', instance=1),\n",
        " Appliance(type='dish washer', instance=1),\n",
        " Appliance(type='electric water heating appliance', instance=1),\n",
        " Appliance(type='spin dryer', instance=1),\n",
        " Appliance(type='electric furnace', instance=1),\n",
        " Appliance(type='sockets', instance=1),\n",
        " Appliance(type='sockets', instance=2),\n",
        " Appliance(type='air conditioner', instance=1),\n",
        " Appliance(type='sockets', instance=3),\n",
        " Appliance(type='sockets', instance=4)]"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Wiring hierarchy of meters"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for m in elec.power_series_all_columns():\n",
      "    print(m, m.chunk)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "AttributeError",
       "evalue": "'DataFrame' object has no attribute 'chunk'",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-7-f9eb6b0cde4d>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mm\u001b[0m \u001b[1;32min\u001b[0m \u001b[0melec\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpower_series_all_columns\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m     \u001b[1;32mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mm\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mchunk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/core/generic.pyc\u001b[0m in \u001b[0;36m__getattr__\u001b[1;34m(self, name)\u001b[0m\n\u001b[0;32m   1934\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1935\u001b[0m             raise AttributeError(\"'%s' object has no attribute '%s'\" %\n\u001b[1;32m-> 1936\u001b[1;33m                                  (type(self).__name__, name))\n\u001b[0m\u001b[0;32m   1937\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1938\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;31mAttributeError\u001b[0m: 'DataFrame' object has no attribute 'chunk'"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Select all fridges"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fridges = nilmtk.global_meter_group.select_using_appliances(type='fridge')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Proportion of energy per fridge"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The energy consumed by each appliance can be expressed as a proportion of the household's total energy.  Here we find the range of proportions for each fridge."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Select a subset of fridges, otherwise the computation takes a long time\n",
      "fridges_restricted = MeterGroup(fridges.meters[:5])\n",
      "\n",
      "proportion_per_fridge = fridges_restricted.proportion_of_upstream_total_per_meter()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Calculating energy for column"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " ('power', 'active')\n",
        "Using cached result.\n",
        "\r",
        "1/5 ElecMeter(instance=18, building=60, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.049"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "Using cached result.\n",
        "Using cached result.\n",
        "\r",
        "2/5 ElecMeter(instance=14, building=61, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.097"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "Using cached result.\n",
        "Calculating energy for column"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " ('power', 'active')\n",
        "Using cached result.\n",
        "\r",
        "3/5 ElecMeter(instance=8, building=63, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.000"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "Using cached result.\n",
        "Using cached result.\n",
        "\r",
        "4/5 ElecMeter(instance=6, building=64, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.096"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "Using cached result.\n",
        "Calculating energy for column"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " ('power', 'active')\n",
        "Using cached result.\n",
        "\r",
        "5/5 ElecMeter(instance=16, building=66, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)]) = 0.083"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "proportion_per_fridge.plot(kind='bar');\n",
      "plt.title('fridge energy as proportion of total building energy');\n",
      "plt.ylabel('proportion');\n",
      "plt.xlabel('Fridge (<appliance instance>, <building instance>, <dataset name>)');"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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mZgEAAJgUzSxL6FoXAD3oWhcAPelaFwB7Zs6QqZDltjSzAAAAjM4yM7O3SPK4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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f1d88ff7d90>"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# How much energy does the largest-consuming fridge consume in kWh?\n",
      "fridges.select(building=61).total_energy()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "active    79.120667\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fridges.select(building=61).plot();"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Z1hqZSd3WSDpB0peU7e3bUqJn00MTwsFpiOHbdX18nom3y8sK121D5buxXJ5j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\ngJ90wjV7TGkr369+tXl/jIyYk0a5nDkmpPKdLYRvtA3fbed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cz/27/52xESdr64mDzsnBcB5fg3Px/ufLN5Eud8ZxHfAH3mOOe7VmHn6nyvHlR8K2sGHrw5FM4l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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f1db97897d0>"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Daily energy consumption across fridges in WikiEnergy data set"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fridges_restricted = MeterGroup(fridges.meters[:20])\n",
      "daily_energy = pd.DataFrame([meter.average_energy_per_period(offset_alias='D') \n",
      "                             for meter in fridges_restricted.meters])\n",
      "\n",
      "daily_energy.plot(kind='hist');\n",
      "plt.title('Histogram of daily fridge energy');\n",
      "plt.xlabel('energy (kWh)');\n",
      "plt.ylabel('occurences');\n",
      "plt.legend().set_visible(False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "Calculating energy for column"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " ('power', 'active')\n",
        "Using cached result.\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Calculating energy for column"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " ('power', 'active')\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result.\n",
        "Calculating energy for column"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " ('power', 'active')\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n",
        "Using cached result."
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Using cached result.\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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wxnXYXwDrmbNH9V8leUSSP8/Qo/rQJP/yXN8IAAAA1rFOofrxJP88w9fS3DHJ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\nDoBJaR0Ak9I6APYorQNg5Fi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       "text": [
        "<matplotlib.figure.Figure at 0x7f1d893d0f50>"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Plot sub-metered data for a single day"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "we.store.window = TimeFrame(start='2014-04-01 00:00:00-05:00', end='2014-04-02 00:00:00-05:00')\n",
      "elec.plot();"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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iIiIiIiJSyZR8i4iIiIiIiFQyJd8iIiIiIiIilUzJt4iIiIiIiEglU/ItIiIi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\n+OPMmDGDffv2sXfvXlq2bBl0WmseY+fOnUlNTWX37t3B17p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LiLVoBFZj4+OPYfLk6o9p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\ngg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f1d89274e10>"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Plot fraction of energy consumption of each appliance"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fraction = elec.submeters().fraction_per_meter().dropna()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "1/10 ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "2/10 ElecMeter(instance=3, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "3/10 ElecMeter(instance=4, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=2)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "4/10 ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "5/10 ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "6/10 ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "7/10 ElecMeter(instance=8, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=3)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "8/10 ElecMeter(instance=9, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=4)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "9/10 ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "10/10 ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec.clear_cache()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Removed building11/elec/cache/meter2/\n",
        "Removed building11/elec/cache/meter3/\n",
        "Removed building11/elec/cache/meter4/\n",
        "Removed building11/elec/cache/meter5/\n",
        "Removed building11/elec/cache/meter6/\n",
        "Removed building11/elec/cache/meter7/\n",
        "Removed building11/elec/cache/meter8/\n",
        "Removed building11/elec/cache/meter9/\n",
        "Removed building11/elec/cache/meter10/\n",
        "Removed building11/elec/cache/meter11/\n"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec.submeters().fraction_per_meter()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "1/10 ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "2/10 ElecMeter(instance=3, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "3/10 ElecMeter(instance=4, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=2)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "4/10 ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "5/10 ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "6/10 ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "7/10 ElecMeter(instance=8, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=3)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "8/10 ElecMeter(instance=9, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=4)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "9/10 ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n",
        "\r",
        "10/10 ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Calculating energy for column ('power', 'active')\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "2                            NaN\n",
        "3                            NaN\n",
        "4                            NaN\n",
        "5                            NaN\n",
        "6                            NaN\n",
        "7                            NaN\n",
        "8                            NaN\n",
        "9                            NaN\n",
        "10                           NaN\n",
        "11                           NaN\n",
        "(2, 11, WikiEnergy)     0.563041\n",
        "(3, 11, WikiEnergy)     0.046288\n",
        "(4, 11, WikiEnergy)     0.010800\n",
        "(5, 11, WikiEnergy)     0.049451\n",
        "(6, 11, WikiEnergy)     0.012683\n",
        "(7, 11, WikiEnergy)     0.130572\n",
        "(8, 11, WikiEnergy)     0.023776\n",
        "(9, 11, WikiEnergy)     0.053165\n",
        "(10, 11, WikiEnergy)    0.103849\n",
        "(11, 11, WikiEnergy)    0.006376\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec.submeters().fraction_per_meter()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "1/10 ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "2/10 ElecMeter(instance=3, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "3/10 ElecMeter(instance=4, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=2)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "4/10 ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "5/10 ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "6/10 ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "7/10 ElecMeter(instance=8, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=3)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "8/10 ElecMeter(instance=9, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=4)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "9/10 ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "\r",
        "10/10 ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "2                            NaN\n",
        "3                            NaN\n",
        "4                            NaN\n",
        "5                            NaN\n",
        "6                            NaN\n",
        "7                            NaN\n",
        "8                            NaN\n",
        "9                            NaN\n",
        "10                           NaN\n",
        "11                           NaN\n",
        "(2, 11, WikiEnergy)     0.563041\n",
        "(3, 11, WikiEnergy)     0.046288\n",
        "(4, 11, WikiEnergy)     0.010800\n",
        "(5, 11, WikiEnergy)     0.049451\n",
        "(6, 11, WikiEnergy)     0.012683\n",
        "(7, 11, WikiEnergy)     0.130572\n",
        "(8, 11, WikiEnergy)     0.023776\n",
        "(9, 11, WikiEnergy)     0.053165\n",
        "(10, 11, WikiEnergy)    0.103849\n",
        "(11, 11, WikiEnergy)    0.006376\n",
        "dtype: float64"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Create convenient labels\n",
      "labels = elec.get_appliance_labels(fraction.index)\n",
      "plt.figure(figsize=(8,8))\n",
      "fraction.plot(kind='pie', labels=labels);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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0PUMEiu+H7cabdeY0B0JEAJ4G9iqHyrHAW0FXIyLBUZ9d/rPM3qybjYf7FeZEpJEdgWuL\nIPU0MCDoakQkOOq3y3uJM2HQb+G5IkgFXYyI5J1RFkRi8PJEqL0RqAm6IhHpfgp0ec06EHr9E+YV\nwWpBFyMieWs7Gz4vgo9/DbU3A17QFYlI91Kgy1/bQPoeeC4Fw4KuRUTymgXsHoG5q8F3I6D23qAr\nEpHupUCXn9aD1PPwf8WwfdC1iEiPYAOTonDXulCegnotZyISIpoUkX96Q9Fz8I9i2CPoWkSkRykC\nni6C0pkQmR50NSLSfbRsSX6JmV0gpm8Cl8aDLkZEeqoPgK2qoGwC8GzQ1YhI7inQ5Q8L0rfC2L1h\nTkq94SLSNU8De/0MlRsBXwVdjYjkllJD3ogeBwOPh2eKQI1zItJV6wF2BObvCrXXAW7QFYlI7ijQ\n5YfRkLoN5qZgraBrEZGCMdaGF9PwzTpQ+2DQ1YhI7mhSRPBWg6KH4caklicRkeyygNtS0HsyONOD\nrUVEckmBLlg2lNwNR5TApKBrEZGCVAo8moLEFcCmQVcjIrmhQBeo5BkwdDT8S4PmRCSHRgLXJKHo\nUaB30NWISPZpDF1wdoT0LHg+Bb2CrkVECt4oC76NwgfbQc3NgB90RSKSPQp0wegPqefgvmLYJOha\nRCQ0dorA/WvAEhvq5wZdjYhkj9ah634OFL8Kp46CP0eDLkZEwuYrYEQVlI8FFgRdjYhkh8bQdbvE\nH2Cj9eEMhTkRCcBA4KoEpO8FkkFXIyLZoS7X7rUxxG+EZzVuTkQCtJEFr8bhq7Wg7uGgqxGRrlML\nXfeJQfE9cGkCBgVdi4iEmgVcm4TEocDOQVcjIl2nQNdtUn+FMWvDYRq3KCJ5oA9wewpSt2f+IyI9\nmLpcu8fWkJwFz6SgOOhaREQyhgCLHfhwJNTcEXQ1ItJ5aqHLvRSk7zbdG9qnVUTyzb/i0HsnsKYE\nXYmIdJ4CXc6lL4JdV4P9gi5ERKQZSeDeIkjMBvoFXY2IdI66XHNrPKQvgCdTWh1ARPJXP2A58M5w\ndb2K9EwaoJ87cUh/Crf1hz2DrkVEpA2VwHqV8N1E4ImgqxGRjlGXa84kTodteynMiUjPkAKuS0HR\nDahLQaTHUZdrbgyG2G3wSBH0DroWEZF2GgbMc+CrGNQ/E3Q1ItJ+aqHLiZKr4fQYrBt0ISIiHXRl\nCqyZwPCgKxGR9lOgy74JULwtnB4JuhARkY4bAJwbg5Ib0ThrkR5DXa7ZlYSiZ+DW3vrjVkR6rtE2\n3NQblnwBvBN0NSLSNrXQZVXyDBhfDLsGXYiISBdEgJuKIHkFGggs0iOohS57hkLsJng0BaVB1yIi\n0kUDgI+Bj4ug7vGgqxGR1ml8RNaUPgWnj4M/KCSLSIFYDAytgqoNgC+DrkZEWqbwkR3bQ+kf4P/i\npqtCRKQQFANlwNsDofbuoKsRkZapha7rLCh5G64YBVODrkVEJMt+BgZVwfIxwNtBVyMizdOkiK6b\nBGsNhilB1yEikgOlwDlxKL0s6EpEpGVqoeuaCKQ/h3v6wy5B1yIikiO1wDoV8O2ewLNBVyMiq1IL\nXZdY02BUqcKciBS2GPDvIiiZhT43RPKSJkV0XhyKHoFbe8HAoGsREcmxEcAtSfjxE+C9oKsRkZXp\nL61Oc46GrZOwTdCFiIh0Axu4vAjSFwPRoKsRkZWpha5ziiA5B+4ohn5B1yIi0k3WBR4Evv4SeCvg\nYkSkEbXQdYpzJIyLwGZBFyIi0s3+lob0eahBQCSv6A3ZcVFIPQA39IL+QdciItLN1gXutOE7jaUT\nySNqoeu4A2FkAkYHXYeISAAs4Pw0FJ+PPkNE8obejB1jQck5cHY66EJERIKzO9BvDWCPoCsREUOB\nrmN2hTXWgF2DrkNEJEAWcFYaSs8JuhIRMRToOqT0XPNLTBtsiEjY7Q/Eh6O1m0TyggJd+20FsRFw\nYNB1iIjkgQhwRhJKzwq6EhFRoOuA0rPgjwmtpyki0uAIC/ztgWFBVyISdlq2pH2GQvQfcFvU7Gko\nIiLmD9ylwJsRqHs06GpEwkwtdO2SPhl+54Amt4qIrOyYKPjTgWTQlYiEmQJd2xJQf6j5pSUiIitb\nDxjtA/sFXYlImCnQtW1f2NIzq6OLiMiqTimGXqcFXYVImCnQtan3yTCjOOgqRETy1x6AMwTYOOhK\nRMJKga51w8HbEPYMug4RkTwWAY6PQfqkoCsRCSsFulaljoUjI5rZKiLSliMjUH8QoB4NkQAo0LUs\nDv7hcLQmQ4iItKk/MN4Fa0rQlYiEkQJdy/aBTYChQdchItJDzExDiSZHiARAga5FvTQZQkSkQ3YE\nIv2AEUFXIhI2CnTNGwR1G8M+QdchItKD2MDUCMQPDroSkbBRoGuWvT9M8iEedCEiIj3M1BjEDgOs\noCsRCRMFumaVHAFTtY2NiEiHbQEUFQObBV2JSJgo0K1qHahfF8YHXYeISA9kAdMTkDwk6EpEwkSB\nbhVOprtVq5WIiHTOwRGwD0GfMSLdRm+2VRQfDgeru1VEpNNGAWvEgG2CrkQkLBToVjZY3a0iItlw\nWAqKpgVdhUhYKNCtxNkf9lV3q4hIlx3kgHcgZqNXEckxBbqVqLtVRCQ7hgFrA4wJuBCRUFCgW2EQ\n1A9Wd6uISLZMSkH8N0FXIRIGCnQr7Aa7uuodEBHJlt9EILlv0FWIhIEC3S96T4K9ioKuQkSkcGwD\n1AwE1gq6EpFCp0BnRKBye9g56DpERApIFBhXB+wSdCUihU6BztgS+tdDv6DrEBEpMJPSULpf0FWI\nFDoFOgCiu8Hemt0qIpJ1uwE1vwacoCsRKWQKdACkJ8HuWnxORCTrBgBrecDooCsRKWQKdFAKFcNh\nbNB1iIgUqIkJiE4IugqRQqZAB+NhdDWox1VEJDcmRCGt5UtEckiBjvSesE9x0FWIiBSubYDyoegv\nZ5GcUaDD2QV2tIKuQkSkcKWAIVXAFkFXIlKowh7oekHVmrBR0HWIiBS4XyfA2jboKkQKVdgD3WgY\nWantvkREcm37GPTWAsMiORLyQOeMgfGpoKsQESl82wJVWwEa4iKSAyEPdKU7wbZaf05EJOcGAgkH\nWDfoSkQKUZgDnQVVm8HWQdchIhICFrCti2mqE5EsC3OgG2z+WhwQdB0iIiHx6zSkxwVdhUghCnOg\nGwNbuUEXISISHttaEBkfdBUihSjEgS61PYxLB12FiEh4bAaUDwISQVciUmhCHOgSO8AYzbYSEek2\ncaBfFbB+0JWIFJqwBjoLyofAxkHXISISMhsBjAy6CpFCE9ZAtzYkPOgTdB0iIiGzZRFEtT2PSJaF\nNdBtCMNqgy5CRCR8RtlQvFXQVYgUmrAGug1gk3jQRYiIhM9IoH5E0FWIFJqQBrr0prCxZlmJiHS7\noUBlXzTTVSSrQhro4pvCBkEXISISQjFg7Ur0S1gkq0Ia6KqHwIZBFyEiElIbg2a6imRVGANdKdQV\nacsvEZGgbFEEMa0bJZJFYQx0w2GdynB+6SIi+WCYDelRQVchUkjCmGqGw8gwft0iInliIMCgoKsQ\nKSRhDDYDYGgy6CJERMJrAFDbL+gqRApJCANdel0YGAm6ChGR8OoPVPYCnKArESkUIQx08XVh7aCL\nEBEJsTiQrgXWDLoSkUIRwkDn91egExEJ2lq1aLkBkawJYaCr7atAJyIStHUsMrMjRKTrwhbobKjq\nBRqLKyISrPViqIVOJGvCFuhWg0SdGb8hIiLBWS8BicFBVyFSKMIW6NaGvrVBFyEiIgOA1PpBVyFS\nKMIW6PrD2n7QRYiIyGqAvVrQVYgUirAFurW0Bp2ISD4oAbzSoKsQKRRhC3SlsFo06CJERKQEcNNB\nVyFSKEIW6KwS6K1AJyISuBKgvijoKkQKRcgCXXI16GUFXYWIiJQCdamgqxApFCELdLHVzV+FIiIS\nrDRQFyN0n0MiuRGyN5Ldy/wSERGRYNlArA79UhbJipAFOisNGrIhIpIfUvWo20QkK0IW6EhCMuga\nREQEgHQ9ZjCdiHRRyAKdnwKNwRURyQ9pH7XQiWRF2AJdQi10IiL5Igqgxd5FsiBkgc6LQTzoIkRE\nBAAHQvc5JJIbIXsjWT54QRchIiJAJtA5QVchUghCFuhwFehERPKFWuhEsiVkYxfUQic9mQdcDRzr\nA5YFtOcQyVcelFbDoCyeMg48AYwD1gGuB8a3cv/BwEPARp14rmmZ5/qmhdvPBuYCT3fi3B3xR+C8\nLp7jOeAU4PUunqcUmAJcmfn/2sAlwP5dPG+2PQecDCwAHgYOApZ3w/MuBNZt4z7HAzOA9YDVgSWZ\n6/cCNgHObemBIQt0eOAGXYNIB/0InAKRWzzL9e1oFKu2zsG3XPyxQDFQDdQ0OmqBOrBqIVKLF6nF\nd+rwbRfLcgEPCw98H8vzwQWr3jzkFxbm0zEOJM0UcT+JWcmxGLMabLFZ3NEqwswfbzha+38S9bGJ\nsSeULYBFWTzlwcAcwM/iOVsyHXiX5gOdDfylG2oA+AMdD3Q2K7duZOv16g38jhWBbjH5F+Zg5a93\nQmBVNO8FzB8ZzzW5/iHgHODvrPyr+hchC3SWulylB3kanBku1rsOxXh2WcT2/HoScVh9dddbvBib\necDe+IxuvjHOB+rAbvbd3xwPEwgrwa+C6szxczUWNVhUY8Jik9AYrcF16vCdOrBdsFwsy8PymwmN\n9ZhAF8OExYQJin4m8PlF4GcCo1UCFINdAlZ7A2MRJjSqHy//xbL/C/kg4LjM5Xrgp8xlB/NBuAPm\nx+4KTHN3Y63d53RMWPSAR4HXgC2BW4FKYFvgA+AOYGfgH8DumA/he4DRwMWYH88aYEegvNFzXw48\nnrn/fZhWmSOAwzEtNWdkrh8IJDCtXv/J1JsE3sCEy0OAqcAJmLfYK5iA5WWe7ypgp8x1LzX5+vcH\nZgG9Ms/9QiuvSRq4HxPgopn6Hszcd0imnicy55uDaQGdjmllSmbuc1/mdSXzfL8HlgFvY/5EPaFJ\nfVtlXsMEUAUcBnyUOe9EzPI3/YFbMMFnMPAY5nu1OfAecGjmsY19nrl9SQuvMZnX7mLgN5nH7w18\nD6yZeU0bWt2OAV6m5e/B97TtzRau94F5wC6YVsVVhCzQqYVO8l0tcC5EL3Gxyhy2wCIB9gtR2+vd\ni8TyH5l8kO+PGIE9Y0YC6jb0eeBNi+99l3E4XU4xNubXbQdW9/FN1e1vdPOgvgbqK6GyEqjCojoT\nFhtaGhuHxlqw6vCjNXhNQ2PjlkbXx3Ix7/A6zC+3GOY3c8KsWeRnAp9fBH4aExpLMaGxOBMa29va\nqNDYdXUr/dNlDjAK8yEPpuVvv8zlIzBhYStMMHkBEzgaa+k+G2KCyFaYn9Bemfsdj+mmXJB5vI9p\nTt8i8//dMtfFMEHvAEyXZppVQ8XzwPaYQNcfExTIXHdb5vLhwFLMj9584G7g/2EC7GaZ+2yYeZ5t\nMW+FWZggejPmx/Zl4NRVXjnDAbbGBNG/YIJpS6/JV5gQVYbpFpyHCXSnAyMb1TO4yXNsAmyKeWd/\nCFyaeY3OyDymHHiG5kPN/zKvh4sJpeex4vs7OvO8VcCrmMDzE7A+JvjNA67FBKsLm5y3cWtdc6/x\nUsxrNy9T5wXAkcDfMvU/m3ktLEznRWvfg62b+bo6Yj7wKxToQC10kr8+BOskn8gTUOr7jMVhJPAI\nFq/H8NZb17er631/+Q/2nntipdOQSlW7lZUfONTdDvOmWXxb47IfDrGgv5Y2NA6Nq7XvIb5pCOxY\naKzOhMYqmg+Nq3ZPrwiN9WDXg+Vh4WLhg2daGi0X0/RTj/kF2tAt3RAaixoFxzRQAlYxHW9pDENo\nrDX/ZCvQrY4JGM3ZBdNK1BAASoChwCdt3GcYpjXtOsxPDpiA06Bpy/idTf5vAcMx3bIN49PKWdXz\nmHFTG2JaknoBawFjMMER4CRgn8zlgZna5jc5z46YQPla5v9J4NvMZRfTWtiSezP/LmBFEGvpdVsE\nnI8JWB5mrFxf2h62+zQrvkfvZ55nDeC/rHhd78IEsaZ6ATdlnt9n5fzyBCZ4NXwdYzEtiF9hghiY\nlrsTWTXQNdbSa1zLihD1OibsghmfOTVz2ceMwzuUlr8HXbUY84dCs0IW6NRCJ/nmRoic4cIih+F4\nbItDfywJZ/wLAAAgAElEQVTqIfof3LplcYeRIzwOO8yOnHyiNWEvvHTafMYfeCDO9ddXAxd41H1j\n89lGLrO/9jkUK/SbKdmsSEXt1OHQ6K4IjRVVQDVWJjiuHBozrYzUgV2DH6ltEhobWhpbCI1Rmu2e\n9lNAOhMaizOhsRTsdKPQ2FbXdMqcM7DQWLvSP1nRWqA4HniyyXWD23GfXVs5b9OxZxXtuE9zFmMC\ny26YiRR9gAMx4a8CM8ljR0zAq8a0CiVaONeNmIkSTVW3UUtN5l+XlbNBc6/JdEyA3jxz/4Wt1NPc\nczR+nqY1tfRan4sJhBMxE16ea+F+Fitabvwm17f29Y+j5de48R8dHiu/Ps3V29L3oKtsWvkaQhjo\n1EInQVsGnAaxmzwitRbbYLE5UJQJE8sgOQuvyoo7bLmly1lnOdGDprvYOAceuOKzd8oUuP5634eP\nbHjAp/5Lh6W7elz5lMVUYEAwX11oOJhUVNT+h3idCI111VDXEBpbamlsPjSSmQjTrtAYX3H4SdPS\n+MuYxkxLI8VmXKPdmYkwzX3q1Zirq5u5qTN+xHRnNudxTHfbs5gveX1WnYzR0n2eBP6MGS9XhRk3\nthTT0tTWtmU+pmuxH2bM3WuYbrlKVm1deBnTSjceE5buAf4vc1tJ5jmrgQ0woaNBwwiDekzgeQD4\nN/ADJhimgS/bqLMlLb0mJZjxYG6m3nUy9y/LfH3t5WO6SC/GBNpyYF/grWbuW4IJvmC6URvbGfN9\nqcaMbzsM87M1CPNavYyZfft8K7W09hq35GngWMx4u4bfCO39HjyNad1raZY0rPq26Qd80dKdwxbo\narL3u0Oko+aCPcPFfsNhbVy2w2EYYDd6034CyVvwq+Jxmx12cPn97x3mzqX+p6+d7bfH7dt3RRiI\nRGDrreGVVyp8mGHB3uA9aVP9J7jxPNgTn421ckmP1l2hscoc5VVAZaPQ2LRrOnPYtSY0RsyMmw6H\nxoaWxkUd+/Bvx1fCu5guzg+b3HYNpjVuAeZD8ntWdK35bdznccy4r9dY0fV2BnADZkB8w6SIltRh\nWtsuw2TbSkwAadqa93zm+s8wXYW9WRFAHsMMuH8/87XNa/S4qzETCV7HTIo4A9MFaWee+3eYMNGR\nmaxtvSa3Ysb7vY15Xf6Xuf9PwIvAO8AjmPFjfqNzNlfDYsx4uPmYiQkf0PwSIv/AtHydgfkeND7X\nfEwAHoAZq9bQbfwhZozhdZiu7CtpWWuvsd/kcsP/T8K8/kdgfv6OwUyCaOl70MDGTAxZwqpOBE7D\njKN8O/O1HpW5bSvM696skP2yX+1RuGI3894S6Q71wN8heqELyxw2w2VrnGbHjs2F2DNQG4/DhAku\nxx/vAMT32NfFX+pcfjkMHbryQ77+GqZOBYh7MNWHazIf5PdAdH+f0b7PTtgFPRBL8p+LaduqzPxr\nuqjhIepwGUT2xhhNx3wQXpCl80n3KMIE3AhmDNy1mFau9piOGbPWdFbsYDq/xmCujcS0IrY0QaU5\nNiaobon5YGn2DiFS/8OKcZMiubQQ2NMnGvfpc6bP7sscTgP2aCbMeeDchkdDmJs82YQ5y4JbbqGm\neqkzZAhe0zAH0L8/9O2LCzUW3OasGHe9L9S9Z/FqEm7FW2nkikh3czCdTn0xnXMbYNq8fCyyu6Dr\nbZh1xULWWNHjnYVZ6uQdTAtle8MctNzyRyvXB+09OhbmwCyZcjcthDkI3Q997F9w9ilmprdILtwO\nkT+68LnD0Ey36gBafqdVQ+JKXPdnnLp4HH77W4/99jN/aNXWEt99om/HK62zzoKttmr+FE88Aeef\nD2YnlBE+vG2v+FutHJyNXEo/tzkUi15Z/WJFOs8Fzv1lgHm+fvCK9Bgha6Gr/RF+ajHdinTOcuA4\niCU8klNg7OcWM4DJOAyk5TD3LaT+hdfrZ+y6eBxOOsn/JcwBXHiRX+NVWqWl+KNHt/zsu+wCkQge\n+JZZI/PqRh+OaXA/dVg6wedKOj80WiTbagCHGhTmRLIiZIGOZfBjNqfIS6i9AvbWHpFS6D/LY2KN\nzanAOOwW59o1eBuSV8Hweqxv43GLP/zBZ/fdV0S/pUuJP/FfqyhhMW0altVGW/quu2IDLlTY8HvL\nTPhrYIM/x6bmbLOK0xv6AJU8UAs4VAZdhkihCFugWwo/qIVOusAD/gnR1VwiY2Cz+T5HA0disyHt\nm1v4MH7RvWYvnTficYtzz4Uddlgpsjl/OdcrpcS3Ij477tj2KY85xjzM/K/GhZnNLLj4Z6h/EB6x\n4VFcreAjgaoB7GbXbRORTgjbsiXLYIk+xqQTvgRm+MQehKQLY7HZGIh3bHmI6LW4vRfj7ADclUzC\nBRfARk0mYX36Kc4779lePO4deCB+NNr2H17pNAwbhvvxxwC1jpnBfxyrLqW0J9R9YLFgM4vvKjwm\nY7drOVCRbKsBrGZ3TRCRTghhC92SkE0Eka65D5xhLpF1YP37PKa4FjOwGI1FvAOnWQ6pf+FuvBhr\nB/DvKiqCSy5ZNcwBsTP/6m7Kpl4ZZfY++7T/PXrccTj80kpX5cM0v/mdUYZB3fc2Xw31uQq/2ZWQ\nRHLNRLn2bFYuIu0QwkD3c/tbVCSkKoGZEEt5JCbBdp9YnAhMwWEwHZ8bvhBSF+PvXwX9LIu7Skos\nZs2CYcNWve8LL+B8853zU+RbdtsNN93WWLxGNtkEiop+SXAWfO3D5S2Ml0uB+5HDz5N8ZmPmUoh0\np5+Bej4IugyRQhG2QPc9LI1rUpU0bwFYYz0iaeh3scfeVTanAb/GbnODn5a8BMkb4TwP/zPHYU6f\nPhazZ8OgQc3ePfH3S9y92dv/yv7Snjy5A925GQccgMMvP+AVNvzJgu9auLcF/j02NX8321a/pjeG\ndKMl1FLHx0GXIVIowhbozN+EWlxYfuEBl0K0r0tkC9jkRZ8jfTgam5F0ZAOlVU5r34lf8oRZqvy6\nSMR/vm9fm6uvtlhrreYfc8cdJCs8+zPrU0ZvidvS3VozZQqsPCO21oXjm+t3beR0qH8MHrdhDm6z\nvbQi2fYT1bSyL6WIdEzYAh2Q/F6/Q8TsNDTZJxbzKTnJZ8cfzJIj++CwZhdPXQPxy3AH/c9s6ndU\nNOq+PWCAxVVXWfTp0/xj6utJXHObfzRHWW/HXrUOObRzUTIS+WUB4kwsq3PgEQfmtvHIXaHuE4u3\nii1uxKOqM88u0gHLAHX2i2RNCAOd84UCXZg9As6GLpF+MOROj8muxUwsxmBlZbbnD2ax4O2Xwstg\njY/F3M+GDrW44gqbklb6bS+5xF/LXd1/n/dZZzDe8OGdL+GEE7BYqW2xEjNBoq6NR65rJkt8vaHP\nlfj81PkaRNq0nDj6ZSySNSEMdDUf6XdI2FQDp0Ms7RKfAGM+sDgBOASH9cjeBnjvQeoK/OPq8G8H\nZ4N43Pt21Ci4+GKbVKrlxy1fTvzhp6yZzLCfTT7sT5vWtffliv1dG68094MH/27Hkj0JcN93KDvI\nTJb4tCuViLSgGvCwQH82iGRLCANd+UfwWVtNFVIQ3gVrvEc0BX3/4fGbCofTgJ2xKc3yUz0Bqbvg\nGuBEcNZJJLxlW23lc8EFDrFYqw+1z/6rt4m/sfs+75Msdtl6666Xc8QROKz0/q5w4Gwbvm7fCfzb\nbGr/DbcDr2iyhGTZz0CU79EMNZGsCWGg4wv4qDroIiRXPGA2RNd2iWwEGz3nc7gPv8ssBJztpbRd\niFyLu9pLZpTalmANSSS8ynHjfM46yyHSxhN+8QWRBW/bJ3CCc0/yZvfQQ8HOwrtyxf6ujdV5cGwH\npjzMgPpn4CkHHtBkCcmiZYCtnYVFsimkgW6hdosoOD8C0yAW90gf4zP+G5tTgEk49MvRU5ZD8kK8\nEV9hvYvpud0wHvdrf/Mbn9//3mlPMoueea67K7u4C1lIlV3p7Lxz1jqAG+3v2qDOhqdteKoDZxkP\ndZ9bvFtqcR2edt6UrFgGuHwUdBkihSSkgW5x631g0oM8Dc5GLpE1YPBNLgfU25yMxbZYJHP4tF9C\n6iL8vSvx54P9ETA6HvfdKVM8jjvOabJ2SPNeeQXnq6+dIzjC+U/scnf//fHa6J3tkJX3d21QacFh\nvtl3qb0GmMkS325sJkv8kL0aJaSWUUetFhUWyaYwBrrvoSqK9oTuwWqBMyFa4hLbCUa/a3EcMB2H\noeT+p/oVSF4H53j4t4HzODAuHsc76iifQw9t93Ij8fMucqcy1fuO7/ie752ObPPVHg37u7LK/l9L\nPPhnB1upY+C+5VA2Df4DWg5WuuRHrUEnkm1hDHQepL9Gfxz2QB+CtZtPNOGz+l89JpSZSQ67YdO7\neyqw7sFPPwr3A6eAfSuwdzyOP3Omz6RJ7X8/3XcfieU1zv7sb1/iXOjtsgtuabYnatB0f9cGlQ6c\nb3fu8/QGi9or4E7gJTwNaZdOWYqHAp1IVoUx0AHWW/BO0EVIu90IkYEukQ1gxOMe032L47HZFIh2\nUwm1EL8ct/878DqwC3A5cEg8DmecAbvu2v6xb/X1JGZd7x3HcSxnOZ84H9mTD+r0nhStarK/ayO1\nHhzVyWkOv4P65+HZiMV9uNR3rUYJoTJiaFFhkawKaaBb9hK8qaVL8toy4EgzySE13WeHRRYzgf1x\n6N/NpfxkFgse8yPWu2CtD5wLnBCPw9/+BmPHdux8s2axRn1vdmRHLrEu9jffHHfttXNRuLHy/q4N\n6m14wYZHOnnWsVD3pcX7feBaPI1gkHarAeqI0PImwyLSCSENdP47MF/z9fLS82Bv7hLpDYOucdm3\n1uZULLbHpiiAcj6A1OX4R9biPw12KTAD/D8nk3DhhbDFFh07X3k58fsf809mpl1PPa/HX7IOOSQ3\nrXMNVt3ftUGlBYf7dHqfr35Q/53Dd1v6zMLXx7O0yzdAnE+g6bI6ItIVIQ10vAPva6Zr3qgH/grR\n3i7RX8GWb8CxwOE4DCe4n9JnIHUHzPLhYnAcYJpl+ZcUFVlceimMHNnhU1p/Pc8b6W/obcqmzGY2\nAwb43ogR2S+9sVX3d22szIO/deGDNQLeqw4VR5tVlT/s/JkkJL7Gp77NzYVFpIPCGugWmb1ntP5C\nsBYCe/pE4z69z/TZbZmZ5LAHDqsFWJYHkRvwes+FZ4Fpmc3B9rRt76aSEosrr4ShQzt+3kWLiL6y\nwD6REx0PjyeTD3rTpnfPe3DV/V0bVDpwkd31Pb6usqi7Bu6y4HlNlpBWfEkFdbwYdBkihSasgc6H\noo81MSIot0NkXZfIerDBHI9DPIsTsdgCCLrdtAISF+Gu/7n56dgK0y801nHcOX36WMyeDQMHdurU\nkT+f6/6a8e46rMO93Eu8qN7aZpss1t6K5vd3bVDrweFe13dhOgLq58HcqMXduGiUqjRnEQCvBVyF\nSMEJa6ADal+Ft4MuIkSWA8dBLOGRnAJjP7eYAUzGYRBkb3+ELlgEqYvw9iiH18Duj0k/m0Qi7otr\nrmkze7bFmmt27twLFuAs/NI5kiMdgDsTN7qHHJKdbb7aa9X9XRu4NrxumcVYumprqFtk8eEaFtfg\nUZ6FU0rhqASqiaDOeZGsC3GgK38NXtfEiJx7BewxHpFS6D/LY2KNzanAOGzSQdfWyGuQvAb+5MLd\n4CQxyxcPicXcdwcNsrjqKos+fTp9+vi5/3Qnc6DXhz7MYx6Vdrmz667dG2Ob39+1QYUFR5GdBbf7\nQv1imx+2hVmYQfAiAIuBGP9DEyJEsi7EgY63Yb5W0MoJD/gnRFd3iYyBzV7xORo4EpsNaXYkV5Cs\n+/GL5sBdwB/BtoByYGAs5n4+dKjF5ZfbFBd3/gkeeojYsgpnMpNtgKtil7r77YcXj2el/A5ZdX/X\nxipcOCtLH7QR8F60qTzB5zrg/eycVXq4r/Go479BlyFSiMIc6BbAwiTqE8qir4BJPrGYT+nvfXb5\nyeY0YE8c1gi6tmbUQWwWbr834VVgQubqH4EB8bj3/cYbw7//bZPswqawnkfi8mu9YznWT5DgUz7l\nW751Jk0K5r3X/P6uDaocuMLO7i4ql1rU3QT3WvCcJkuE3heUU8+8oMsQKURhDnTVUPwhvBJ0HQXg\nPnCGuUQGwbD7PKa4FjOwGI1FAK1Q7bLULBa85fdY74C1YebqRcA68bj385gxPuef7xDr4iyN2bPp\nU1tk7cIuFsDFzoXejjvmZpuv9mh5f9cGNT4cloUJEo0dAvWvwYsxuFOTJUJtMRHM308ikmVhDnRA\n5eMwt5PbH4VdJTATYimPxCTY9hOLE4GDcRhMfkxyaMnHkLoUf1oN/n/BbhgZ9yEwJJHwKnfc0efP\nf3aIRLr2PJWVJO6a489kpuXgsJSlfOT8z54yJdhO5+b3d23gWfCOBf+X5WfdHOq+sfmkH1yNx/Is\nn17y33KgHh9t+SWSEyEPdNXPwZPatKhDFoA11iNSBGtd7LFXlelW3RGbkqBra4fnIHkrXOLDLHAa\nIttrwMh43K/de2849VQnG9NPrfP/7g/zh/hbsiUAl3Cxv8nGuAMGdPnUXdLy/q4NKiyzsnNZlp+5\nD9QvcvhpnM+VwNdZPr3kt8VAlLfJbvOviGSEPNDxEixIoN3F2+ABl0G0r0tkC9jkRZ8jgWOwGUXe\nTXJolgfOLXi9noMngd82akN8Dtg6HvfdqVN9jjnGbmGfrI759ltiL8y3ZjDDBqillvmJ5zl0Wn68\nWs3v79pYlQt/zEHrtQ3esw5Vv4cbgHf04R4aX+NSw7NBlyFSqMIe6JZA4lt4K+g68tS3wGQzyaHk\nRJ8dfzBLjuyDQyeXYwtEFSQuxh3yCdZbwHaNbnoA+HU8jnf00TB1atbeD5E/n+Nuz/bueqwHwDVc\nQ79+vj9qVLaeoWta3t+1QbUD1zq5W3z7Aqi7Ax60LJ7C0yIWIfAF5XgatCySK2EPdID3LLwQdBF5\n5hFwNnSJ9IMhd3pMdi1mYjEGi0TQtXXQYij6F97Oy+ENsAY1uulGYJ94HP+UU3wmTszeqL933sH5\n+DPnaI52ADw8Hk/e323bfLVH6/u7Nqj2YXqWJ0g0diDUvQ2vJOB2PGpz9DQSPA/4hgTaIUIkZ/Lm\nAyY4ZU/Bk1q7hGrgdIilXeITYMwHFicAh+CwHvk9yaElb0LyajjVxX8AnFSjmy4BpsfjcOaZsPPO\nWf3q4mf/3d2P/bzVWR2AB3mQSLLO2m67Nh7YzY4/vqX9XRv4lpkqclMOu0VHQd13Np8N8JmNz8+5\neyYJ0DeAzQ+YkXQikgMKdPACvOCEd5zuu2CN94imoO8/PH5T4XAasDM2AS2tkRVz8Ivuh9uAs8Bp\nnNjOBmYkEvC3v0G2U9YTTxD5ablzMAf/8t66PXGdO3UqOHkxem6FAQNa29+1QYUNJ1mwLIeVlID7\nhcOSXc1kiUU5fCoJxke4uNwbdBkihUyBDr4AtyJcS9l7wGyIru0S2QhGPedzuA+/w2ZjoIurdQSq\nHmJX4a75GswD9mly84ngn5VMwoUXwhZbZPe5PY/ERVd6R3Gkn8QsRvwKr1BmlTm7756fbZwt7+/a\nWLULp+V4eR8b/Mdsqs80feFvhfYvrML0HhXUZ2WzYBFpgQKdaZp7EOaE4APkR2AaxOIe6WN8xn9j\ncwqwLw79gq4tC342iwVv8i3Wu2Bt1OTmqZblX5ZOW1x2GYwYkf3nv/56Smvi1gQm/BLerope6k6a\nhJfI07GHre/v2qDGgVsdWNANFZ0DdffCHBse12SJglAGLCWKBiuL5JQCHQDl98Jd2V50K488Dc5G\nLpE1YPBNLvvX25yMxbZYdGFXq7zyKaQuxp9cjf8i2Ks3uXkP2/ZuLS21uPJKGDIk+89fW0vitvv8\nkzjJcjLD0haykMXWYmffffP7fdb6/q4Nqn2Y5nXPnuoToe49i9dScAsuNd3wlJI7nwBRngPtESKS\nS3n9QdONnoV34rA06DqyqBb4M8RKXGI7weh3LY4DpuMwjML6zr8AyZvhHz5cC0600U0esI3jeI+u\ntprF7Nlm4FgOWOdf4K/rDfLHMOaX6y6xL/LGjcPt3TsnT5k1re/v2sC3YCFwTTe1ZG9gJkt8sS5c\nhV9Qb82weZ9yqrO+9YiINFFIH+tdUQlF8+GJoOvIgg/B2s0nmvBZ/VyPPcrMJIfdsMnzYNFhHti3\n45U8BY8CxzWZi1sPbBSNui/362cxe7ZF3765qeOHH4g996I1k5m2lSlhGcv4IPKuffDB+bGQcGva\n3t+1QYUNp1rwU7fUBWlwP3FYtqfPVcAX3fS0kj31wEKimLeoiOSQAt0vlt4B9/bgbcBuhMhAl8gG\nMOJxj+m+xfHYbApE23xwz1MNiUtxB3+I9Saww6o3MyQadd8fNMjiyistcthM5vzlHG8MY9xhDPvl\nusu4zB85CnfQoFYemEda39+1sVoXZnbj/sc2+A/a1PwVbgYWaLJEj/IVEOFz4LuAKxEpeAp0KzwM\njzhtNlLklWXAkWaSQ2q6zw6LLGYC++PQP+jacug7M/lh3DJ4C6x1m9y8HBgUj3tfDh9ucdllNul0\n7mr54AOc/31sH8uxv4ShWmp5OfEs0/Jkm6/2aHt/1wY1Dtzt0O0L/v8J6ufAozY8gqvJEj3Eh9RS\nq+5Wke6gQLfCF+B8B/ODrqMdXgB7c5dIbxh4jcu+tTanYrE9NkVB15Zj70DqSjipHh4Gp2lU+wEY\nGI97P2yyCVx4oU0yt7M+Yn85z53IPt6ajfZCu4EbWGNN39+o6TTbPNf2/q4Nqnw41O/+P34mQN1H\nFm+kLW7Co7qbn1467n1q8Hgw6DJEwkCBbiU1d8ND9UFX0bx64K8Q7e0S3R62eAOOBY7AYTjh+E4+\nip+6B64H/zywm37JXwLrxOPe8m228TnvPJtYLLf1PPsske+XOFNZeQ/YR5L3eNOnY7e+V2r+aXt/\n119Y8LUPswLo/hxiJkt8NcznSnyWdH8F0k5LgCo8ume9G5HQC0MM6IDq++HOqqCrWNlCYE+faNyn\n95k+uy0zkxwm4LBa0LV1Exei1+Ct/grWC8ABzWxE9j9gaCLhV+28s8+ZZzo535bB80j883LvCA73\n06xoJ3yIh7Djtdb22+f26XOhffu7Nqiw4Q9WMEOjUuB+5LB8P5iNeYtI/vkYH5tH6Z61bkRCT4Fu\nZS/Bd/XwXtB1AHdAZF2XyHqwwRyPQzyLE7HYAshxw1NeKYPkv3BHLoJ3gc2aucurwEbxuF83caLH\nySc7q7bd5cCtt5Kusq292GulcHlr4lp3ysH5t81Xe7W9v2tjdS6cENygU/8ui5p/wK3Aq5oskXfe\no4wa7g66DJGwUKBbmQf+TXBzQN2uy4HjIJb0SB4EYz+3mAFMxmEQzbRLFbjPIfVv/ElV8DLYazZz\nl6f5/+zdd3wUdfrA8c/MJNkNVRAVxBNQETlEQTjQU852ov7ALjZEEUVOUIrl1PMUFbuCoEhRVLCA\n7bBgAVGRohSlo4KAgHSkJ9lsm5nfH99Zs4RNsptszT7v1ysvtkx5NmR3n/m2Bzq6XLZ5ww02t95q\nRNtnWCV+P+4J79oDGKDlhNVJW8hC9rHP6NIlc/+noqvvGuI34DMDZic8rrLdA8Ev4UsDpmBm1Jym\n6swHbMYNTE91KEJkC0noDuKZAK/7ohobHjfzQTvVIqcuNB5lcZlX527gLHQSOEEzrc2F/PHwuIX9\nJhiuCJtMBs5zubD79oXrrkve3/LQofZfzCPt0zn9gIdH5Y4wL70UK8HzMBIuuvquIR7gRju1RQDO\ng8BajWV1NMZjkWaDJrLSz0Auc1BXqUKIJJCE7mBLwLsbvk/waSzgWchtYJJzKpwy36YP0BudlkTd\n6VUd6e9h154GnwADQY/U3PU6cIXLhX333TYXX5y8FrE9e3B9OeuARYQBNrKRTdpG48orM/89FV19\n13DbbRiR4nFSTdRkiS2t1GSJnamNJuv9SAFeRqU6DCGyScZ/+SSADcWvwIQEVZDcCFxuk5dnU/ff\nNuft0rkHuAiDwxJzxozhB9cLmH/5WU2L+2cZmw0DerlcMHgw/POfSe3eNAYPMdvRzmxJywMef14f\nanXqhHloNZmoEl191xCPDoN12JLQmCrmBnOFwf7u8DKwNsXhZKu9wHZ04NNUhyJENpGELqLAW/BO\nnLuRPgSjuYlxNDT/0OI6U2MgGh3QiNSfmG3+gBrPYv19N9oy0I4rY7MHgbvcbnjySTjttGRGCGvW\nYCz/ybidfge0nxZSyM85SzOizFe0oqvvGi5gwW1pMoLtLQ3/cJgEzMOS6RJJthQTnXdRI+mEEEki\nCV1k68BYU/Xarh5gEOTVsHBfDn9fozEA6I5BU7JvkkNZfoIao7BvC2BPB71OGZv1A/uxGjVg2DBo\nG2m+a2LlPfS42ZWuZiMaHfD4C4ywT2iJ2ax0yYoMFn1915CADl8ZappKOhgAwW/h6xyNj2WyRNLY\nwEKK8fNKqkMRIttIQlemfWPgNU/l9l0EWieLnJrQcLjFxcWqW/VcdMrKVrLVdKjxPrxsw3PlrPZx\nnaZZo2rX1hg5Elq2LGOrBJozB2PrdqMnPQ8IMUiQ793fZFSZr2hFX981xAPcZIM/USHF6EwIrNNY\ncQi8hkUl380iBpsBLwUkvzacEFlPEroy2e+p2q4FUW5vAS9C7uEmOe3g5Dk2vYF/oXMiWT3JISIL\ncl7HrP8dfAt0L6e98gJdtyYdcojG6NGQomYw91PDzZ70tGtT+4DHJzCB+g0s2rRJSVgJFX1913C7\nLHg2jRaSPQqC2w22tbEZhc0fqY6nmluIF5OxJHeZACEEktCV5w9wz4ZJFXwwbQOuVZMcave3OfcP\nteTIpRhEWjhNQCHkD8U8YQPaCuBvZWxmAR0Nw5rWoIHG2LEajRsnMcgw77xDfpGtX8qlByWdn+a/\nb93YEy3TynxFK/r6riEeA57QVSG2dJEH5mKDwpvUZInVqY6nmvKhVv82GZfqUITIRpLQlWvvczC0\nMCEvOX4AACAASURBVPL32edg/NUkpxEc+47FNabGnWicioY76YFmjt+hxjDsrkXwA+iNytgsCLTK\nzTUXHHmkSuYOS9EU4GAQ97i37f7coeWVKtHxBV9g5/n0M89MTWjJEEN91zB+E25Nw1Frr2kERsO7\nwHcyWSLufgIMvkd1vAohkkwSuvJNhy0e+NG56wXuhbxaJnld4NRfNG4HemBwDDLJoSILIP81GGxh\nvwtGWXmvF2iWl2eubNpUY9QojUMOSWaUBxo+3G5kHmafycFZ2xuul83rrsPOyYmwXzWRkwN/U02o\nMSRoQQPm6PBFgqKqin9BcA58m6sxGZMU1YSpluZSgJdhcTyiC5iJ+mRtCswIe24SsBQYEGG/PkCP\nCI83BZZXIZ5vgSYVbNMNldqawClhj58EvFqFcwtRoWr8VRQXFniHw4OD0Xx55MzUqWdbnIHBX4Ec\nSYijpX2IXXMp2vvABeVcSOwHjnW5rJ0tWmg8/bSOO4XNnfv34/r8a20Qz2haqWx9KUvZq+01unZN\nUWxJdMcdaD16xDoKtEiDXjas00i7JuvTIfC7xi8nwh+7LHqgUzPVMWW4rcBe/MDUOB61O2otu9Jt\nqQ2B9kDzCPsYwNg4xhDOjhBLacuByyLEsAw4Fjgc2BH/0ISQFrooBF9Fn+aixbc2vWzoi85JSCoc\nrQDkjcRsvFS1c15QzqY7gKNcLmtn27bw3HOpTeYA/ZEh1sn2SWZrWh/03Mjc582LLsKqUSMFgSVZ\nbPVdw+234PE0miARriEEtxns+JuaLLE91fFkuB/xYfESMbXkVuha4GPntgnscm5/CTQGFgNnoFrO\nngd+QLXYDQbucrZth2rJWwL0DTt2DeA9VGvaZGCesy1AZ1SpoIXONqF0fzcVv76VwK9lPPcFqgVP\niISQhK5if5DLBzQGyhrwJSLbpRYL7rhTLRbcopxNNwBN3G6r4IwzbB57TCc3N1lRlhHQBnIWLdfv\n4I6DWqY2s5nftQ1Gt27Z8/6Jrb5riMeAoXr6lmzIAWuBQdFtMA71VSxi5weWYWPGde05AziRkuRo\nI3Clc/si1B9VW2AOqtUsFzW/KtTlG2pJex3oB5Seh94XlSC2Qq1X3s7ZpwHwAHCu89hC4E5nnyuo\n2vjABcA/qrC/EOXKmi+kKvHxNHPxyeKkMVgJNUZi9/JjfwN6vXI2/Qlo7nLZ3s6dbf7zH6Ps1eiS\nJ/fBIeYFnG8exVEHPTdcH2b9/e+YqZqnkQqx13cN8Vtwi5Xeq1iM0gi8Ch9oMEsmS8RsCTYGc4BN\ncTxqA8peMyrSaOV3IzxW1/mZ49x/M+y504F3nNs/obpEAU4F/opqoVsM3AAcHXXU5duKGscnREJI\nQhedhZisliv4KH0DNd6BF214EYzyeqfnAye7XHbgyittBg400NPgT3L+fIyNm41e9DoosyykkOW5\ni/TYx5Rlvtjqu4aYOvygwScJiSl+ekFwPszOg/cx41r1rzozgZkU4+XBBBw9lmlmRZU4Xln3p6Na\n/9qiWvB6xxBHReeXywWRMGnw7ZkhfDzOnKhXGc5OFhhvYB0yC74CelXwgTwdOM3lwuzZ0+aWW/RK\nrI+REO4nhpnXc71Vl7oHPTeKUTRvjnnMMSkILMVir+8aUqSp78R0L9XwNwhs1vn1cHgFS97tUVgG\nBFmBGoMWTzuBWlXYXwP2AXtRrXGgJlmEfAdc5dz+K9AalWzNc7Y/1nmuJpEnX7xB2UtohscQrhFq\ndIkQCSEJXfQ+ZCd+tqQ6jDTlAfcwzOa/oS0HTqtg8w+A810u7Ntvt7nmmvT5O5w8Gdd+v9GNbgfF\nZGExyz3N7tkz+1rnoDL1XcMVmvBwmk6QCNcAglsNdp5hMxrVSSYis4AZFOHj/gQc3UQtU1zW0NuK\nWrpCz98EvITqPg1/fBRwGKq7dYjz7z5UItmTkmVRvi8jhtZEHk93GWq836nAZxy4dk8HYFYFcQtR\naenRJJIpdO6jBQ9yNVkwtzEGm6HGa1jnmdgTwajolzMO6O1ywb//bXPOOenzNxgM4r7wcuvO4B36\neZx30NNv8AbTjnzdfuut6lsZoiJLl8LAgZXdOx/1vVre9Jh0Msgmd7jGpdi0ks/Kg6wAprACHyeR\nmK7EnsARwNMJOLaOmkjhQ7XGTQeOh6hWJqwDvAJcHeM5v0W1CsqyJSIh0qdlJBNYvMRqTKkHGWYR\n5L8C95nwYRTJ3HM4ydzDD5NWyRzAqFEcFqzHuZwb8emP8idZPatxma9oVK6+a4jPgpvSfIJEuOc1\nAm/BR5rGDJkscQAb+IZCp3UuUb+ZiUAXEtPwUBM1WWIJatmS24gumQO1XGasydxJwBokmRMJJAld\nbAqweYqv034wUFJoH2PX/ERNL3sQ9Io+dR8A7nG74amn4NRTkxBhDAoLcX001b6TQboe4W0xnemY\nOV797LNTEFuaib2+a4ilwzIN3o97TInTHQKL4HsXvCOTJf70K1DEdlS3YqL4Uct8JCJhLECNgWsD\nnAxMS8A5wi0DbknwOUSWk4QuViYvsJZgVi9EGoS80ZgNF6tZqhdFscu/wH6iRg0YPhzalF4SKvW0\nx56wWtktrTYHLVeljHeNMa+5tnqX+YpW5eq7hhRp8C/KXpEiHbWBwFadtUfCWCz2pzqeFCtpnfsP\nmdPcKkS1Jwld7AoxeZyvo5omX/3sUYsFn7IdbTloraLY5SpNs8fWqaMxciS0SMPxUxs3kjt/kd6f\n/hEnO6xgBbvYbVx0kYyjgsrWdw1XbMIDGbaqYz0IbjTYfQ6MJrvLz68D9rAX+F+qQxFClJCErjIs\nRrKOINtSHUiSrYYaL2Bf78OeBfqhUezyT8Ow3q9XD0aPhmbNEh5iZeQ8NMQ8h3PMJmXU3X4xZ5jZ\npQtmraosolDN3HEHGpVawgTAa8A4Q42qzyQ6WF/rFN8H44HlWdo69Q2F+HmQ+Jb5EkJUkSR0lePB\n5FG+yqJWulmQ/zYMs2EsGBUV5rKA9jk55tcNGmiMGaNx5JHJiDJ2ixaRs36j0ZtbIiYn29jGen2d\ncfXV2blUSVkqX981xGtDzwyaIBHuSQi8Bx9rGtOxKvsbyEgbge0UA2+nOhQhxIEkoassi9FsIFDt\n16WzwHgbq+43atRwnyhmnAWBE3JzzYVHHqkxdqxGGtfIcg151ryGa6z61I/4/PPaUKtjR8zDD09y\nYBmgcvVdQ2wNVmrwZiZmdEA3CC6HBfkwEQt/quNJkm8oJMgjINNDhEg3ktBVXjFBBlfrVjovuIdj\nNluNthToFMUuxUCTvDxzdbNmGqNG6dQ9uNpC2pgyhby9RcbVXB3xfeDBw7K8H7OyzFc0Kl/fNaRI\ng/6aWsw/E7WCwDad9UfbjMHO2JcRra3AJoLYvJrqUIQQB5OEripsXmYjvmo5QHqbmvxwzn60JaBF\nHl12oL3AUS6XuaVlS40RI3Rq1kx0lJVnWbhHvmrdxm22G3fETUYximbHYDWPVPhHAJWt7xrOZ8K9\nGTwWqw4E1xnsucBmDKpLsrr6Cg8mTwDeVIcihDiYJHRV4yXIQ3xFYaoDiaslkD8G7jSxp4AeTVq2\nDfiLy2XtbtcOnn1Wxx05SUobY8dS319T60zniF3IFhYz86faPXvKe6Q8la/vGuI14E2jpDJTJtLB\n/kLHOxgmAEsycmBg+dYAG9mHxYupDkUIEZl8WVWVzTg24as2V+afYdf4CN4ChoARzR/IOqCpy2UV\n/uMfNo8+apBb0ZSJFPN4cL//qT2IQZpRRi4yiUnUqmuGlucQZahafdcQrw03WpWeX5E2HobgR/CZ\nDtMwM/7lhASBTyjCTx+kdU6ItCUJXdX5CHAPn1GY0dflJuS+jHn4D6oa9eVR7rYcON7lsn0XXmhz\n//0GRvoPN9OefMpubh9nt6d9mdtMzn/bvPHG7C7zFa1+/TCoUiudrcFvwKuZ/A5yXAKBnzV+rKHx\nFia+VMcTBwsw8bEI+DTVoQghyiYJXXxMYA8bWZahKd0+qPEs5slb0FaAdnKUu30PtHG57OBVV1n0\n729UoXxA8mzbRu6cBdpABpT5tz+DGfiNYuPcyCVdRSlVq+8aUqTDXRrsik9QKdUCAtt1NjSD0djs\nSXU8VVAAzMCPj95k5hozQmQNSejiw8JHL77Am3FX5L9BzRHY3bzwHejRLjAyFTjD5cLq1cumV6/M\nSOaAnIceNf9BJ/MYjilzm1ddo8yrr8ZK957jdFL5+q7h/CbclcETJMLVAnONwb5L1GSJDamOp5Km\nUwy8AqxKdShCiPJJQhc/87CZwswMWpHqO8h/A5604HUw8qLc7V3gQpcL+447bK66KnP+hpYvx1j9\nm9GHPmV2D65kJTvZaVx6qbw3YlG1+q4hPgPeM2BBPEJKAzrYH+n4noA3gYUZ1sK1CfgFHwEeTHUo\nQoiKyZdWPPkYyAKCad9rZIH+Dlad6WpQzB0xfBePBa5xueC++2y6dMmMZjlH3iNPmVdypdWABmVu\nMyJnqHnBBVLmK1ZVr+8aUmzDDXb1qip1PwQ/h6k6fJYhkyUsYAqFBBgE7E91OEKIiklCF19bsRnC\nFIrS9lrcB64XMY9eibYYOCeGXZ8B/uVywaOPwllnZVQyx5dfkrdrv9Gd7mX+zf/BH/ymrzGuuUYW\nEq6MqtV3/ZMGm2wYna7voEq6EAKrNZbU0piAlfZzRZdhs4cNwBupDkUIER1J6OLNZBhb2MkvqQ4k\ngu1qseB/7IFloJU9iuxg9wH3ut3wzDPQoUOiIkwMy8I9bLTVm952PvllbjZcG2a3b4/ZsGESY6tG\nql7fNaRIh/s12BGXuNLHMWqyxKYWNqOx07Yl3wtMxYufXmT+WjJCZA1J6OLPj58eTMGTVhMklkON\n0dAviD0VjNox7Nob7Kdr1oQRI+CkkxIWYsK8/jp1fS6tC2V3EXvxsihvvnbDDdI6VxVVq+8azm/C\nHdWp39VRA8yVBvuvUuMX1qU6nghm4sfmY6rPYEYhsoIkdIkxG5OP+CpNUrpp2DX+B6+C/UyUiwWH\nXKlp1rg6dTReegmOPz5hISaM14t74mR7IAPLXEQYYAxjaNLEtlq0SGJs1VDV67uG+A2YYsCcqh8q\nHdnvavifg7eBBWk0QGMn8AMBfAxMdShCiNhIQpcofgawBB9bUhiDCTmvYh06F20WcA1EPe7NAs4x\nDPN/9etrjBkDTaKp5pp+tKeesZtZTeyOdCxzGwuLb/I/tW+UMl9xUfX6riHFQE9blSqoju6C4Fcw\n3YApmCmfB2IDn1KExSPA9hRHI4SIkXyBJc5OggzkQ4pSMgqlAPKHYv51I6wA2sWwqwW0z8kxZxx2\nmM7YsRqNGiUoyAT74w/yZn6vDWKQrpWTy77He+TXNulYds4nYlD1+q7httkwohqP4zoXAms1ltXR\nGI9FcQpDWYzNFrZhMSKFUQghKimahM4FzES17jQFZsTx/OOBK6Lcti5wWxTbRTMq5XZUuWkLqB/2\n+MUQxzWXbMazn5+Yk+Qmhg1Q43nsSzywAPRYxvj7geNzc83FjRtrjBmjceihiYoy4YzBj1qncqrZ\nnOblbve//DfNG24AXS5v4iI+9V1DinR4SCelTd2J1gQCO3S2tLYZhc3OFISwG/iCYvxcChm0lqYQ\n4k/RfIV1Ry1XlohxHrEcsx7QN07nnQOcy8Hrt09BJZjxqhFg4+NKZuNN2vfRPMh/HR61sCeC4Yph\nVw/QNC/PXHvMMRqjRunUrZuoKBNv5UqMX1brt3FbuS1Fs5lNse4xzjsv+u5oUbGq13cNFzChX6o7\nJBPMBeYyg4Ie8DLqcjNZTOA9irB4ENWgL4TIQNEkdNcCHzu3g5QUW2wFzAcWA0uBY53H70TVbF8O\nDAg7zg3OdkuACWGPh5K6IcDrTkz3oGZYLQUedp5/yjnHYuBpoCEwy7m/HDjd2S6atQ6WELkYjw3M\nBTpHcYxobSRAb97Fk+jrXv0DrFpT4SPgLtBjyVD2AEe5XObWVq00RozQqVEjQVEmR97gJ8zLuNQ6\ngiPK3e6VvJFmt25YedGWyRBRiU9915CAAV8a8E18DpfW3tDwvwDvAHOxkjJdYjYB9rAMk+FJOJsQ\nIkEqSugM4ETgV+f+JuBK53YfYATQFjVEa7Pzb0+gA3Aq0Btog0r+HgDOdu6HJ3oa8CxwKHAT8E/g\nOOcYoWN3Au4F1jqP3Qtchyop2hY4CZX8AeWMfo/OAuAfVTxGae/g5QumJmg5Ub9aLLjxCrSFxJ6N\nbgH+4nJZe9q3h2ee0XHF0q6XhmbMIGfHbuN6ri/37/tXfmU7O6TMV4LEp75riAc1QSIbegPvgOBM\n+CZH4yPMhA7Y2Ax8hxcfVyFrzgmR0Sr6ImsAFJTx3FzgP8C/UWPrvMAZwGTU9LQi53YnVCL3Hmqk\nBsBe518NNWatDiXdqZ2dn8XAQqAFKsEr3eD0AyoBHIxK6AoreC3R2uK8nvjycTPLKYh7ietdarHg\nU3ehLQct1oVF1gLHuN1W0Vln2TzyiEFOTpwDTDLLwv3sSOtmetm1KL9+1whjqNW5M2Ym9yyns/jU\ndw2324LnsiTp+AcE1mv8XA9ew8KTgFP4gXfxEKA36mJdCJHBommZKOsjeRJwESp5+xyVtNmlti/r\ndoiNSszaocbIhTyJanlrCxyP6ootbTYqWdyMmlzRo/yXETWdxIwX3EeAK/iQ4rilnj9DjZHYtwaw\nvwY91rxkCXCC2237unSxufdeA6MarKn79tvUKta1i7m43FRiJztZY/yqS5mvxIlffdeQIgMe1+H3\n+Bwu7TWGwDaDbW3VZIl4F86YihcvXwDvxvnIQogUqCih2wllNnM0Q80ofRE1xq41Ksm6FMgHajq3\nZ6EGv3SjZEZpePI2FTU+7jPnXNOAXs7+AI2Bw1AtheEFDo4G/gDGOT9tI8T4NVDRmhulv/gbEXl8\nXTzMxuQlJuOpcsr4NeS/pypePk/sqdgcoJ3LZQevucaiXz8jzk0pqeH3457wrj2AAVoO5bc0jtCG\n223bYjZunKTYslSc6ruG8ZvQp5pPkAiXB9Yig8Jb4BVKBr9U1a/Acgrwc3OcjiiESLGKEjoTNesp\n0vr5VznPLUaNkXvDuT0eNQ5tHuojaCnwM/A4avmTJcDQsOPYwAfOtp+gksKJqC7dZcD7qERvF/Ad\nagLEM8BZzrEWObGUXjtJR02i2M3B+gMbUcniMtS8spAOqCQ0MQI8wCZ+58dKjlexIGc8Zv3Z8C1w\nQwyLBYd8DvzD5cK65RabG2+sHskcwNCh9l/Mxvbpf86PicyPn4Wu76XMVxLEr75rSNCAWbq6Dswm\nr2gExqqBK3OqOFlCDYYpJkA3YF984hNCpFo03+Q9gSNQM0szSSvUGLu7Y9hHRyWI7Uns8vQnkMtC\nbqUGh8WwVxHkj8JsVoT2JeiVaVyaCHR3uWDgQJsLLqgmmRywezeuK7rzPMNoSctyN32RF1l27GTr\nlXEyGSIZvvwSnnwy3kdtZMNvGrjjfeA0Nxdyz7RpEbC4FKOChuiD2cDbeNjAywQYlIgIhRCpEc0X\n2kSgC5VoCUqxn4gtmQPoimotTPRCwCsxuYd3KYr6TJugxlDs/yuCHyuZzI3CSebuv796JXOA/vAQ\nsz3tzIqSOQuL6fmfWFLmK3niV9813D4LnsySCRLhToPARo2VDTTGYcU8HncxNr+zhQD3JSQ8IUTK\nRPOl5kct45E+BaQT5xPgsaScyWI0Bczn6yjWYfgB8sfBfy3s98HIr8TpngD6ud3w2GNw5pnVKplj\nzRpylv9s9KNfhV2ok5mMq2ZQ+/vfkxGYCIlffdcQjwHP6tEVhqlujoDgVp0dHdVV2rYod9tFeDUI\nX+LiE0KkgrRSpI6Nj6v5kX38VHayrH2EXfMzNZDw/hgXCw65C+wH8vPhmWegffvKR5ym8h56zOxK\nV7NRhfNf4F33BLNHDynzlWzxre8a4rfgliyaIBEuB6x5Op5+Nq8CKyvY3Ae8SREm96B6L4QQ1Yx8\nraXWTgJcwEcUs73UMwHIewmz0RK1rkuXSp7gZrCH1aypMWIEtG5dxXDT0Jw5GFt3GD3pWWGyMJe5\nePRC4/zzM274QMaLb33XEFOH+bpqWM9WIzUCr8MHGswsY7KEBbyPBw//w2J0siMUQiSHJHSpt4gg\n/+JNPH8uHroHajyH1f4PtVhw+aPCynaprluv1amjMWoUNC+/QH2mcj81wuxJT7v2ASvaRDY27wXz\nyiuxMr0QRqaKb33XkCINetskZOXdTNETggtgTh68h0mg1NMzCfA7q/HTm+wYOiNEVpKELh3YvImP\n8byLh1VQ4wXsG33YM0GvX/HeB7GAMw3D/LhePY2xY+Hoo+MdcXp45x3yiyz9Ui6tsMVtLWvZyjbj\n8svlbz5V4lvfNVyhBY9k4QSJcO0hsFln9RHwCtaf9X1WAt+zHz8XkB1104TIWvLlli4CDGAza9yT\nYIQNo8CoTBEuC2ibk2POOvxwnZdf1mjYMN6RpodgEPe4t+3+3KHlkVfh5iP0Yda550qZr1Rz6rvG\nOfnyGPCiHr9VdzNVAwhuMdjZyWYUasXOyXgI8H9EP3VCCJGhJKFLH0GCXKLDrsr2CPqB5rm55rK/\n/EVjzBiN+pVp38sQw4fbjczD7TM5s8JN97CHVTk/69ddJwsJp5pT3zUBYxh9FtxkSY+iDtYsg+Jb\nbT4EAtyJWuhdCFHNSUKXXtZ74Kx/gWdujDt6gCZ5eeZvxx2nMXKkTp06iYgvPezfj+uzr7VBDNSj\nyQ1GMMI++STMo45KQmyiXPGv7xpi6bBUU8tIZjsfsMSDVWMkNmNTHY0QIjkkoUs/KzxwzYVQ/FuU\nO+wGGrtc1rYTT4Thw3Vq1EhkfCmnPzLEOpmTzdZUPGvXj58F7lnccKO0zqWL+Nd3DSnS4F/w5wCy\nbGQDPb3wyyzwDEh1NEKI5JGELj19Wgz3nQ2eSIVow20C/uJ2W3s7dLB5+mmDvIrHk2W0devIWbRc\nv4Pbo0oIxjGORo1s+8QTEx2YiFb867uGKzbhv1m6Nh3AowH4bB0UXElCfr9CiHQlCV2a8sMLO+G1\n86HIW8Y2q4Fj3W7Lc9ZZNg8/bJBTmWkUmSV38GPmBZxvHkXF/acWFtPyP5IyX2no5psxSMjnT7EB\nrxjZuXbuJBue2QcF55Ld67gIkZXkiy6NeWDAKvjmKigufam9GPiry2X7L7rI5t//NrKi9MH8+Rgb\ntxi96BVV69wnfEJOfkA7/fREByZilZj6riFeG3pm2QSJucAtHvCcC2xNdTRCiOTLgiwgo1kFcNW3\nsOJ28IW+nmYB7V0uO9i9u03fvgZadhQ+cD8+zLye6626RLf2yCT3a+b114Mho+fSUvzru4bYGvyi\nwdtZktEtAc4vBk83YFmqoxFCpIYkdOnPWwCd34TfB0PgE+AslwurTx+bHj2y5/9v8mRcBX6jG92i\nes3zmU+BVmBceKGU+UpXianvGlKkwR0a7EvM4dPGcuDMYijqAXyR6miEEKmTPQlBZttbCJ2eg12X\n5OVhDxpkc9ll2fN/FwziHj3e6kdfollEGGBM7gvm5Zdjud0Jjk1UWmLqu4bzmnBfNZ4g8TPQqRgK\nbgLrf6mORgiRWtmTFGS+7cXQBU3bi8+XXbPXRo3isGA9zuXcqDZfxzq2aFukzFcGSEx91xCvARMM\n1SVZ3awEzvBA4a1gv5vqaIQQqSdfeJllET7f3xg1ah9ffpkd44MKC3F/NNW+k0G6HuWf6wh9mHXW\nWZjVuVBGdZG4+q4hXhtutKrXCh6rgdOLYX8/MN9KdTRCiPQgCV3mWYPPdwbDhu1nxoxqn9RpQx63\n/mq3tNrQJqrt97KXlTkr9O7dZSHhTJGY+q4htgZrgdeqyXtlLfB3D+zvD+b4VEcjhEgfqUroXMBM\nQAOaAjPieOzxwBVRblsXuC2K7dZFsc3bqH6Q5cCrQGhRuIuBB6OMJ1q/4POdydNPFzJnTpwPnUY2\nbiR3wWK9P/2jTs5e5EW7VSvMo49OZGAinhJX3zWkSIe7NFVTJZOtRyVz++6G4LhURyOESC+pSui6\nA5+SmIWiYjlmPaBvnM77FnAC0BrIB25xHp+CSjBz43SekKX4fOfw2GOFzJsX50Onh5yHhpjncI7Z\nhCZRbe/Hzzz3DCnzlWESV981nM+EuzJ4gsTvwGke2HsfBEanOhohRPpJVUJ3LfCxczsI7HJutwLm\no9bNXQoc6zx+J6rlazkQXp/wBme7JcCEsMdDSd0Q4HXU67wHWOBs/7Dz/FPOORYDTwMNUcu8LXbO\nFVqSdkcUryl8yYAf4M9SBjZq1c/OURwjVj/i853Hww/vr3Zj6hYtwlj/u9GbW6JOzsYznsMOt+2T\nTkpkYCIRElffNcRnwLuGemtmmk2oZG7PQ+B/MdXRCCHSUypqRRnAicCvzv1NwJXO7T7ACGAiKrYc\noB3QE+iASszmo7prA8ADwGmovpRDws6hAc8CNYGbUMnUcWHH+BjoBNyLSiLbOvvdCUwFnnCOUdN5\nvGMMry8XuB7oH/bYAuAfwGcxHCda8/D5TuP552eyZ089rr66WrROuYY8a17LtVp96kd90fF5/v+s\ngTehZ8k6y9VKqL7rjh1oJOxCs9iGG2xYoSc0d4yrLahkbvej4Bua6miEEOkrFS10DYCCMp6bC/wH\n+DdqbJ0XOAOYDBQDRc7tTsDZwHuUDIzZ6/yrocas1aGkO7Wz87MYWAi0QCV4pb/6f0AlgIOBk4DC\nSry+UaiE87uwx7Y4rydRfsbrPYXx4zczerQfO8Mb66ZMIW9vkXE1V0f99zmFKeguv9apUyIDE4mU\nuPquf9JgIzAmQ94gm1Fj5nY+Bd6nUx2NECK9parLtaw2lEnARajk7XNU0maX2r6s2yE2KjFrhxoj\nF/IkqiWuLXA8qiu2tNmoZHEzanJFj/JfxkEGA4eiWvrC6SS+sORGvN5TmDJlFU884cXM0OFCiBBm\nFgAAHSpJREFUloV75DjrNm6z3US/KvDb7lfN67pLma9Mltj6riFFOtynwR+JPU2V/QS09cD2x8E7\nJNXRCCHSXyoSup1ArTKea4aaUfoiqlu0NSrJuhQ10aCmc3sW8A3QDQitNhaevE1FjY/7zDnXNKAX\nJV2ojYHDUC2FtcP2Oxr1ST/O+WnLwb4GGkV4/BZUK+B1EZ5rBGyI+IrjaxfFxafx/ffzufdeD15v\nEk4ZZ2PHUt9fS+tM56g7ThexiP3sM7p0kTJfmS5x9V3D+U0YkMZXPDNxuln7gPeJVEcjhMgMqUjo\nTGAFqtuztKuc5xajxra94dwejxqHNg94BTWx4WfgcdSn3xIgfHyJDXzgbPsJKimciOrSXQa8j0r0\ndqG6RpcDzwBnOcda5MQyolR8OmoSRaT1D0YDhzvnWAz8N+y5DqgkNBmK8HjO4+efP2fAgCIKyurd\nTkMeD+73p9iDGKQZMYxxGpU73LzkUqz8/ATGJpIisfVdQ/wGfGwcOCoiXbxjw/8VQsHFsmiwECIW\nqWrR6AkcgZpZmklaocbY3R3DPjoqQWyPmtGbLDpu9wjq1evFiBE1OOywJJ66crT/PmSf+N0+6wVG\nRP2FvpGN3JJ3AxMnwqGHJjI6kSy33oq5ejWQ8MTuWBtWaqmZGxbJcyYM3guec1AXnkIIEbVUjaGb\nCHQhdQllZf1EbMkcQFdUa2EykzkAC6/3DnbtGsKtt3r4/fcknz5G27aR+90CbSADYvoSH64PtTp1\nwpRkrvpIbH3XcNtseDENJkiYwO1+eGQjeE5BkjkhRCVkWkIlKsMwbsLtfolnn82nZctURxNRTu++\n5llrGvMAD0T9RV5IIVfmXcToMdCsWSKjE8nWtStmUVEykrqaqNqokYbFJsN+4DIP/LAUCroAe1IU\niBAiw0kt12xgmq9TVHQVgwZ50nIB4uXLMdb8ZvShT0xf4C/ygn1CS0xJ5qqfxNZ3Dec3oV+KJkis\nQ81kXfAOFJyJJHNCiCqQhC57fIrP15Hnn9/KiBE+gsnuAS6b6+GnzCu50mpAg6j3CRLkO/fX3Chl\nvqqlxNd3DQkYMM2IbznpaMwB2hbDpvuh8BbUQulCCFFpktBllxV4vSfy5Zfz6N+/iD1p0CDw5Zfk\n7t5vdKd7TH+LE5hA/QYWbdokKjCRSsmp7xriAXra4E/8qQCYYMP5hbDvMvC/QOLXqBRCZAFJ6LLP\nHjyec1m37iV69fKwalXqIrEs3MNGW73pbecT25ojn+a/b93YE03KfFVfia/vGm6nBUMT3MXrA+7w\nQb/t4OmIWh9TCCHiQhK67GTi9d7L3r09GDiwiClTrJSUC3vtNer6XFoXusSUln3BF9h5Pv3MMxMV\nmEgHofquJGUsnceAx3RVGiwRVgFtimDCDChqhVpHUwgh4kYSuuw2Ga+3PaNHb+DRR4spLk7emb1e\n3JM+tAcyMKZFhAHecL1sXncddk66LB8mEiYJ9V3D+C3oE+cuXht4zYZ2HlhzNxT8H5EXJhdCiCqR\nhE6spLj4RObP/4hevYpYty4pJ9WeesZuZjWxO9Ixpv2WspS97DW6dpUld7JBcuq7hgR1mKnHryd0\nH3CFBwash6IOEByDjJcTQiSIJHQCwENx8XXs2NGfvn09TJuW2C+dP/4gd+b32iAG6bFOZByZ+7zZ\n9SKsGjUSFJtIO8mp7xri0aCXrca7VcU84AQPTJ8Eha1Qi5ILIUTCSEInSljWa3i9pzJ8+CYee8xL\nYWFCTmMMftQ6jVPN5jSPab/NbOZ3NhhXXSV/t9kkOfVdw+214MlKtgqawGNBOHc/bOvuLEmSqLEM\nLlQtaw1oSnzXXhkPXBHltnWB26LYLpbm/xeA8ELUFwMPxrC/EFlHvhhFacvxev/K999P5LrrPMyd\nG9+jr1yJ8cuv+m3cFvMX9HB9mPX30zEzoCytiKNataB5c0yS10pnwDN6bPkHwGbgjCJ4Zgl4WgEf\nJSC4cN2BT0lMN24sx6wH9I3judsDh5SKYQoqwcyN43mEqFYkoRORFFJcfDMFBV159NFtPPJIMfv3\nx+XAeQ89bl7GZdYRHBFjQIUsz12kX3+9LCScjZJX3zUkYEHvGBLIKcBfi2Hpc1BwKrApUZGFuRb4\n2LkdBHY5t1sB84HFwFLgWOfxO4Hlzs+AsOPc4Gy3BJgQ9ngooRoCvI76vrgHWOBs/7Dz/FPOORYD\nTwMNgVnO/eXA6c52O6J4TQbwDPBvDixNaQNzgc5RHEOIrCQJnSjPDLze45g3bwLduxcze3bVjvbN\nN+T8sdu4nutj/rsbxSiaN8c89tiKtxXVz8knQ82ayWqhAzVBYp6uErXyeIG+Prj2D9h/HhQ/THJa\nEg3gROBX5/4m4Erndh9gBNAWaIdqOmwH9AQ6AKcCvYE2qOTvAeBs5354oqcBzwKHAjcB/wSOc44R\nOnYn4F5grfPYvcB1wFTn/kmo5A+IagbU7agkdVuE5xYA/4jiGEJkJUnoREWK8Hpvo7CwM088sZn/\n/tfD3r2xH8WycD830rqZm+1a1IptVyxmuafZPXtK61w2S15915AiDW6xVSWJSGYCxxfBW9Oh6Hjg\nu+TFRgMOHGMWbi7wH1QrV1NU1nkGMBk1nq/Iud0Jlci9R8lSKqE3t4Yas1aHku7Uzs7PYmAh0AKV\n4JWe2fQDKgEcjErooh2MeyQqKR0Z4ZgAW5zXI4SIQBI6Ea05eL3NWbhwHNdfX8w33xDTYsRvvUWt\nYkO7mItjXm7kLd6ibn2LU06JdU9RnSSvvmu4QguGlEoidwLdi6HLLth4PRRcREkilExl/S4mAReh\nkrfPUUmbXWr7sm6H2KjErB1qjFzIk6iWt7bA8aiu2NJmo5LFzajJFT3Kfxl/aoNKENcAvwE1KGmB\nBPV9Jcu+CFGGdEnoop2t9S0Q+lr/DHX1WJb1QP24RBe9qp6zKdHNVHsN2I4anxJuGOqDNFGK8XoH\nUFR0Ns89t4H77/ewO4o1Uv1+3G+8Zw9ggJZD7KsBf5Q/yeopZb6yXnLru4Z4DBihw2pULjHehmOL\n4ZPxUNSMxE98KMtOKLOpuxlqRseLqO7L1qgk61IgH6jp3J4FfAN0o+RzKzx5m4oaH/eZc65pQC9n\nf4DGwGGolsLaYfsdDfwBjHN+2kaI8WugUanHPncea+b8eFBJY0gjYEMZr1mIrJcuCV20s7XCn+8C\nlDdSv/QVaTJU5ZyxZDqvAxdEeHw0atByos2nuLgFS5a8RI8exUyfbpfbWvfcUPsvZmP79D/HRkfv\nK77CzPHqZ59dhWhFtZHc+q4hPguus+C0Iuj/K+zvBIV9KbvLMxlMYAWq27O0q5znFqPGyL3h3B6P\nGoc2D3gFNbbtZ+Bx1AX1EmBo2HFs4ANn209QSeFEVJfuMuB9VKK3C9XdvBw1oeEs51iLnFhGlIpP\nR02iqOhqsPSHSgdUEiqEiCBd2jymA/1QzetHAcNRYynyUcnLScBK1BiLvqgPivWo1jofagxIY9QH\n/aOoD5p1qBlbF6GmundDFVQM9ylwP+qDaDFqXMkQ5xi/o7ouPkZdteYC/0V9sNWM8Zw1UVfLrZzH\nH3aO0xO43HleR3VNjCC69Z+aokZsty71+DLUwOFkdQG1Iz//XZo1a8igQTU57rgDn929G9cV3Xme\nYbSkZcwH7+66wux642792mvT5m9VpNjVV2Pu2IFG8i5I/ZCfA4EHIfgMakZpOugJHIGaWZpJWqHG\n2N0dwz466nO/Penz+xciraRDC115s7VuQw2o/StqgG27sP1CV28XoMZqtEElN+F1e/5w9hlN5A+P\n0FiPOkAA+Lvz+BmoK1YvcJlzjHMouXqN9ZwPoLoYOjrHeRY1PgRUd8QVqHEum4h+Mc+yLAZOq+Ix\nYrGQ4uITWLXqHm6/fT9PP+0N74bVBw8x29POrEwy9xM/sYvdxkUXSTInSiSxvquN6vb7CIqPguAT\npFcyMRHVU5Fp74+fiC2ZA+iKai1Mp9+/EGklHRK68mZrdQLecm4vR7U+lbYMOA811uMMDuyGnez8\nu4jIs6Nmo1qzTqdknEg+avzGatTv50lU18R0VAvh4ZU4Z2fgPlSyNQM1ZvBo1BfGdOLbmpaKmWBB\nTHM0Pl8Tvv32Fbp3L+btt01++YWcFb8Y/ehXqS6yF3KGmV26YNaKbVKsqOaSVN+1CNW6/k/gamBr\ngs9XGX7U51c2TBT4BHgs1UEIkc7SIaGD8q8wK7r6XI1q5VqOesOHl4cJFWQ0iTxG7QdUE34n1NiM\nJcCtwI/O891RCecpzjl2AO5KnvNySmaHNUV1IYP64ognjdR9wO/F6+2P13syEyfOyOk7wG5LG6sh\nDWM+0Da2sV7/zbj6almqRBwsgfVdvagLtDtRPQdxLpUihBCJkQ4JXXmztWahFqkE9eF6UoRtGqE+\nhN8GniPyjKqyBFDdnN2A71EtdndTMvC2DiqJM1Fdok0qec5pQP+w+6Hty0tWGwNfRfMiSmmEGl+Y\nSqvxeM4LErhlOcvX3szNhUtYEtMBnteGWh07Yh5+eIIiFBktAfVdfahlPl5CXXC9TFJn0wohRNWk\nQ0JX3myt0ahk72fgEUpazqCkFao1JWVuHiJys7xN2a1Ws1BLgPiAOahu1VBJhLdRLXjLUBMWfqnk\nOYegJkMsc17rI1HE1Yiyx4tMQiWgxwMbUQOMQ9qSPq0Kr3nwnLCOdX3u5/4dAxlYtPLPhsmyefCw\nLO9HvUcPaZ0TkcWxvmsAdXH2Bmrm5d3AnioeUwghki5dBtP2JDNnayVSP9SaS5/GsM/xqBbDixMS\nUdW4dPRb8sgbciIn5t3KrTWb0zzihs/xHL+1/MwaNSotLjhEmlq6FAYOrPTuJmoM2seome7r4xOV\nEEKkRrokdHmo7sUzyY4BvokyDDUpY06qAymH28C4LYech1rTOvcWbqnZIqxx1sLikvzO9oMPm1qH\nDimMUmSErl0xi4piaskNOj9foMpjVdxkLIQQGSBdurRMIpeQEbGZhlo/L50Fbex5JuYL29i2dzrT\nT13EIrMhDfOO4AgmMYn1DRbSv79UhhAVCwbRlyzBouKL0yAlLXJXAaNQ43eFEKJakK9MkWpuDe0G\nN+7BDWlYZ3f+5hp97vDrF16Y6rBEJggGoXNnbNsu87PMD1jA/1BrWa5NWnBCCJFE6dJCJ7JXEFgY\nJDhiL3t/0XPM85Yvx87JIadpU7Tc3FSHJ9KZrsPPP8PmzVgcOMmrCPW3NQ61/NBryGQHIUQ1Ji10\nIh2dVrMm/zVNzunSBf2yy8hr3DjVIYl0tWkT9Ojx591C1ELdT6HK8BWmKCwhhEgqSehEOmvqcjHI\ntrnpuOPg8sup3akT5OWlOiyRLjZuhI8+wv/hh+TY9p8lpb6ChFeSEEKItCIJncgELuCSWrUYZJq0\nOf989IsvJq9Zs1SHJVLB74fvvoMPPqBg7VqwbV7x+3kJ+C3VsQkhRKpIQicyTbO8PPpoGrc2bkzO\nFVdQ++yzIT8/1WGJRLIste7cF19QPGsWem4uSwsLeR74kJJye0IIkbUkoROZKge4sFYtBvr9nN6+\nPcHOnanZsSO43akOTcSDbcPatfDllwSmTiVgWWwpLmasZTEJ2Jzq+IQQIp1IQieqgwbAZbVr08vn\no+3f/kbwvPMkuctUW7bAjBlYn31G0d69+EyT1/x+JqBKAAohhIhAEjpR3RyGSu5u9vk4uUMHldx1\n6CDJXboyTbX0yHffEfj2W7x792IbBh96PLwKfIdMcBBCiApJQieqs8Nxkjuvl5ObN8fbqRO1O3RA\na9YMpBJF6hQVwY8/wsyZeObNQ9d1tgYCvOf38yHwA5LECSFETOQrLTYu4EvgLKAJqlzZ2ZU4ziuo\nuqu/VDKO9cApwO5K7l+eb4EbgQ3lbNMNeBg4AfgbsMh5/CRgAHBzAuKqqjrA2fn5XAJ0ycmhVseO\naKedRn67dlC3bqrDq96CQfj1V1i2DHvOHAp+/RWX282iggLeBj6l/L+3VIrXez6S8cAUVBWLitQF\nrgNGV7DdOqCi+d+vAu1QCzGvBXoC+4CLgZOBIVHEI4RIMzmpDiDDdEd9+dhVPE7vKu4f6fxaOc9F\ny3D2r+gYy4HLgLGlHl8GHItqGdtRhTgSYT/wcXExH6N+V8d99RXnz59Pt+JiOjZujK9DB/Jbtya3\nVSuoXz/F0WY4vx9WrYKlS7Hmz6dw1SrceXlsMU2+9HqZBkwPBChIdZxRiNd7PpJYjlkP6EvFCV00\nBsKfv/uhwB3AY6jk8lHUosyBOJxHCJFEktDF5lqgn3M7COxybrdClRbKQ131Xg6YwFTgR1Rr2k/A\nDUAxqhXsTlTLViEwHOjqPHcJBydDhwKTgCOBuZQkb02BacA81BX3e6gP/kHO872Bls65rkd9cOcB\n81FfDpZz/jHAP53XttuJvTwry3nuC1QL3ksVHCOVbGA1sLqggJGAa8MGTt+0iU7TpnFecTGn1KqF\n2bo1tGlDrRNPhGOOAUMK5ZVp1y7VArdqFeb8+RStWUO+283vgQDTfD6mA7MDgT/fL5kklvf8WtR7\n7SZnm3HACOf2DcBdqL+9pahWcChJ6oYAR6Fat+9CvYdcqGVZHkYlWccCi1Eths+j3u+1UZ/j/0KN\nN4zmQiqUzGlAPuq9EIplLtAZ+CyK4wgh0oh0uUbPADYBjSI89wIqqZqI+nDNARqiFjo9HfUh+Spq\nlt5QYAbqQ3sRKqm6CPUB+jSqJenxCMffgbqK/j9Ui0EDVDfiWuA0YAFQE/Vl0QKVlH0H3Oqc42lU\nq5oJjHJietN57irgg0r8TsJfR8jZqC+XqytxvHSho36Hf69Rg3M0jU5+Pw2POQZPy5bkH3ecWtS4\nSROoWTPVoSaXZcHWrbB6Nfz6K+ZPP1G0di25gQCW280vXi+z/H6+Qf3t7U11vFUU63u+FapLtiPq\nb2g+6kIqAExGvU93A4egfjevo97Lp6Leu31RydQVQB/nGB8DzwC/O9u2ds5/J+AGnkB9jtcktjJn\nrwMXAmtQ3clB5/GbUEMp7o3hWEKINCAtdNFrAGV2Ec0FHkBdYU9GfUgCbHSeA3gL6I9K6ML5Kbka\nXgicF+H4nVDJGMDnHFhkfAMqmQNVkPwbVIK4EshFtQzejmrB+9HZLh/Y5tw2iW4MT7S2oloOM5mF\nGt/4izPTEqDeqlV0WLWK1rVq0VHTONnjoWmtWvibNsVs0YIaxxxDTtOmcOSRUKtWZk+6KC6GzZvV\nz5YtsH49xevW4d+wgXxdpzAvj2VFRcw2TRaiWo02+v0J6ZZMpVjf82c4t4udbSaj3rs2qjUtNOY1\nlOhqwIOoxK+P81hn52exc78mcBzqsyTcD6gWwlzgI9SFXCxuQiWMI53X8Yjz+BbgghiPJYRIA5LQ\nxaasr+hJqKv1rqiEqw9qcHL4F5xG5DEz4WNVLMr+Pynr3EWl7o9DfUD/gvrAD5kA/CfC/t4y4qqs\nsl5nptuD6t6eVljSDqLv20ezpUs5cdkyTqxVi462TWuvl0aahla/Pt4jjsA+6ijyjjyS/MMPh4YN\n4fDD1SQMlys1SZ/XC3v3wu7d6t89e2DXLuz16/H8/jvBbdvI83rJyc9nq66z1utlmd/PSlTX3FJg\np9eb/LhTJJb3vF1q+7Juh9ioxKwdaqhE6ELtSeDlUts2LXV/NipZ7IqaXDEM1eIeCwt4B/h32GM6\n1fP9K0S1Jwld9HYCtcp4rhkqgXsROBrVLbLOuX0q6oP/OtSHcGXMcvZ/HNVNUq+cbRegWg3aUtI9\n8zWq6+Z54A+gvvNafq/gvG+gXtMP5WxT+ouqEek7YzHeLFSX91rb5uOCA9ty6m7fTpPt2zl62TKa\n5OZyTH4+LWybZoEAjfx+amsamtuNr2ZNgrVqYdepA3XrYtStS+4hh+ByuyE3V/3k5Kh/NQ10Xf2r\naaoL1Oc78MfrxSwuJuj1Ynq9WAUFWLt3Y+/bh1FYiMs00Vwu9uXksFvT2G5ZbPF6+S0YZDWqpWkt\nsLWwMOuXDon1PT8blVw9hUqMLqWky/VDVNK1mwOTt6moC4XPUC1z01Dj6d5GXaw1RrXiF6DGy4Uc\njaqWMQ411q4tByd0Xzvn31rq8eNQ/88aambr4rDnsun9K0S1Igld9ExgBWps1apSz10F9EB9cG9F\nJV6HONv1Q7WU/UTkGWp2qduRro4fQbUIXAt8z4EfuJG2fw+1/MA+5/4vwH9Rg6l1J86+qISuvKvx\n1kQusXQZagxRA9QX0WJUognQAZWAZrt9qFm/ywACAfVTSn5REfWKiqi3Ywf1UIl2PaCeplEvN5c6\nhkG+ruPWNPI1DZemocMBP6ZlUWRZFASDFAQCFNg2xYAH1fVXjEoGdgDbnX8LioulFSYKsb7n96IS\nutAQiFco6Qp9HJjpHHMR0Mt53EYNeagNfIIaIzuRkqEahaiZtutQ4xKXoyYerQDucc5fgJp0EU5H\nTaIovbSR5sRYx7n/IyWTPkC9f6cc/KsQQojqpSfRDxZuivrwTYUpVH2trDrAu5XY71vUsiVCVAc9\nycwJAq2A52LcRweWIBf6QogskIdqfYpm5FNTnNaZJAq1ClYmEYuHk1BdQEJUF7G85zPdxaiWfCGE\nEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCGEEEIIIYQQQgghhBBC\nCCGEEEIIIYQQQohs4gJmoupXNgVmVLB9U2B5Jc91I9ConOcfAc6N4XjPAiuApysZT6Ksi2Kbx4Hf\ngYJSj/cHesQ9IiGEEEJUa72Ae5zbTUlsQjcDaFfGc3oljreX2Aqp51TiHJURTULXAWjIwQldbWBB\n3CMSQghRbVTmC1NUf9cCHzu3g8Au57aBagFbACwFbo2wb3nb3AssA5YATwJXAO2Bt4FFgBtYDzwF\nLAS6AeOd7QD+Bnzn7D8fqFXq3J84jy0CrgJeD9sXoND59yxgtvMafwLOBL4F3gd+Ad4K2+dB57Us\nB8aGPX4c8JUTy0KgmfP4PWGv/eGw7XdQsQXAtgiPF6D+D1pFcQwhhBBCCAxgaxnP3Qo84Nx2AT+g\nWueaUtJCV9Y2F6KSMbfz3CHOvzOAU8LOsQ64O+z+68DlQB6wlpLWvFpOrKWFt26VTuhCz52FSu6a\nhN3fCxyJat37Hjjdea5e2P5vAF2d2/OBS5zbeUA+0JmSpE8HpgCdIsRYkdItdKC6nm+rxLGEEEJk\ngWR1N4nM0YDICQWohKU1cKVzvw6qpWpNBds0R42Dew3wOo/vDdundBfpu6Xua0ALVKK50HmskKpZ\nAGwodX+Lc3sJKgn9DjgH1epWA6iPGp83E5X8hVox/c6/nZ2fxc79mqjfz+wqxooT2zFxOI4QQohq\nSBI6EUl5Y9BuB6aXeqxpFNucX85x7VL3i6LYJhpBSoYV6KiWtLLO4Qu7baJa/9zAS6hWwc3AYOex\n8mJ5Eni5ErFWRKvgvEIIIbKYjKETpe3k4LFpIdOAvpRcCByParmKZpvpwE2orkko6cosQLXilccG\nVqFmw7Z3HqtN5C7XcOsp6aK9GMitYPvSQt3Du1C/k27O/UJgEyVdri7U65qGmlBS03m8MXBYhOOu\njDEOUK99fSX2E0IIkQUkoROlmahuxRYRnhsH/IyadLAcGE1JUmVXsM001KSFH1Fdknc5248HxlAy\nKaIsAeBq4EVUl+i0MrYPb8V6BTXhYQlwKgd209qlbkdq/drrHGMFMBU1bi6kB2o5kaWortkjUEnr\nRGAuavLHexycHDco4/UBPANsRCWHG4GHwp7rQHy6boUQQgiRJXqiZqSK+OuC6pKORR3U5BIhhBBC\niKjlAbOIbT03kTj9getTHYQQQgghhBBCCCGEEEIIIYQQQgghhBBCCCHE/7cHhwQAAAAAgv6/doUN\nAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA\nAACAQzeDmGc4NwL2AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f1d8f175f10>"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Select meters on the basic of appliance category"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec.select_using_appliances(category='heating')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 20,
       "text": [
        "MeterGroup(meters=\n",
        "  ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])\n",
        "  ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])\n",
        ")"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Find all appliances with a particular type of motor\n",
      "elec.select_using_appliances(category='single-phase induction motor')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 21,
       "text": [
        "MeterGroup(meters=\n",
        "  ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])\n",
        "  ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])\n",
        "  ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])\n",
        "  ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])\n",
        "  ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])\n",
        ")"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Training and disaggregation"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Train\n",
      "co = CombinatorialOptimisation()\n",
      "co.train(elec)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Training model for submeter 'ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])'\n",
        "Training model for submeter 'ElecMeter(instance=3, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=1)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Training model for submeter 'ElecMeter(instance=4, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=2)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Training model for submeter 'ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Training model for submeter 'ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])'\n",
        "Training model for submeter 'ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Training model for submeter 'ElecMeter(instance=8, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=3)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Training model for submeter 'ElecMeter(instance=9, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=4)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Training model for submeter 'ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Training model for submeter 'ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Done training!\n"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for model in co.model:\n",
      "    print_dict(model)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<ul><li><strong>states</strong>: [   0  887 2970]</li><li><strong>training_metadata</strong>: ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d89775e90>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [ 0 13 77]</li><li><strong>training_metadata</strong>: ElecMeter(instance=3, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d801a7b50>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [ 0 11 12]</li><li><strong>training_metadata</strong>: ElecMeter(instance=4, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=2)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d80191c50>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [   0  197 1030]</li><li><strong>training_metadata</strong>: ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d80191b10>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [0]</li><li><strong>training_metadata</strong>: ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d80191cd0>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [  0  15 520]</li><li><strong>training_metadata</strong>: ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d80191e90>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [  0  34 789]</li><li><strong>training_metadata</strong>: ElecMeter(instance=8, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=3)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d80191e10>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [ 0 49 52]</li><li><strong>training_metadata</strong>: ElecMeter(instance=9, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=4)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d80191bd0>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [  0 138 463]</li><li><strong>training_metadata</strong>: ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d80191f50>"
       ]
      },
      {
       "html": [
        "<ul><li><strong>states</strong>: [ 0 17 34]</li><li><strong>training_metadata</strong>: ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f1d80191b90>"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Disaggregate\n",
      "disag_filename = join(data_dir, 'wikienergy-disag.h5')\n",
      "output = HDFDataStore(disag_filename, 'w')\n",
      "co.disaggregate(elec.mains(), output)\n",
      "output.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "vampire_power = 321.0 watts\n",
        "Estimating power demand for 'ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])'\n",
        "Estimating power demand for 'ElecMeter(instance=3, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=1)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Estimating power demand for 'ElecMeter(instance=4, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=2)])'\n",
        "Estimating power demand for 'ElecMeter(instance=5, building=11, dataset='WikiEnergy', appliances=[Appliance(type='dish washer', instance=1)])'\n",
        "Estimating power demand for 'ElecMeter(instance=6, building=11, dataset='WikiEnergy', appliances=[Appliance(type='spin dryer', instance=1)])'\n",
        "Estimating power demand for 'ElecMeter(instance=7, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric furnace', instance=1)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Estimating power demand for 'ElecMeter(instance=8, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=3)])'\n",
        "Estimating power demand for 'ElecMeter(instance=9, building=11, dataset='WikiEnergy', appliances=[Appliance(type='sockets', instance=4)])'\n",
        "Estimating power demand for 'ElecMeter(instance=10, building=11, dataset='WikiEnergy', appliances=[Appliance(type='fridge', instance=1)])'\n",
        "Estimating power demand for 'ElecMeter(instance=11, building=11, dataset='WikiEnergy', appliances=[Appliance(type='electric water heating appliance', instance=1)])'"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Examine disaggregated data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "disag = DataSet(disag_filename)\n",
      "disag_elec = disag.buildings[building_number].elec\n",
      "disag_elec.plot()\n",
      "disag.store.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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iIiIiIiJSyZR8i4iIiIiIiFQyJd8iIiIiIiIilUzJt4iIiIiIiEglU/ItIiIi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\nf+kI4LVr17Jw4UJ+9atfUVJSwrBhwxLqyKdNm8a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rKePGo24kpId4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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f1d801c39d0>"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Calculate accuracy of disaggregation"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "disag = DataSet(disag_filename)\n",
      "disag_elec = disag.buildings[building_number].elec\n",
      "\n",
      "f1 = f1_score(disag_elec, elec)\n",
      "f1.index = disag_elec.get_appliance_labels(f1.index)\n",
      "f1.plot(kind='bar')\n",
      "plt.xlabel('appliance');\n",
      "plt.ylabel('f-score');\n",
      "\n",
      "disag.store.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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9rInegq/yrc3P17Mdt2fHfeTrWe3lO5fzncf5OoZsPdtxH/l6tuP2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\n3NrvA78KfA1wgHpRvJdQtxK8NS7WUG4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       "text": [
        "<matplotlib.figure.Figure at 0x7f1d89775e90>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 26
    }
   ],
   "metadata": {}
  }
 ]
}